US20090216639A1 - Advertising selection and display based on electronic profile information - Google Patents
Advertising selection and display based on electronic profile information Download PDFInfo
- Publication number
- US20090216639A1 US20090216639A1 US12/334,416 US33441608A US2009216639A1 US 20090216639 A1 US20090216639 A1 US 20090216639A1 US 33441608 A US33441608 A US 33441608A US 2009216639 A1 US2009216639 A1 US 2009216639A1
- Authority
- US
- United States
- Prior art keywords
- entity
- content
- profile
- electronic profile
- web page
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Abandoned
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
- G06F16/258—Data format conversion from or to a database
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
- G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
- G06F21/6245—Protecting personal data, e.g. for financial or medical purposes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0207—Discounts or incentives, e.g. coupons or rebates
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0269—Targeted advertisements based on user profile or attribute
Abstract
Description
- This application claims the benefit of U.S. Provisional Application 61/067,162, filed Feb. 25, 2008, entitled “Platforms, systems, and methods for data handling,” which application is hereby incorporated by reference in its entirety.
- Embodiments of the invention relate to computer systems and software for advertising selection and display based on electronic profile information.
- Advertising systems presenting advertisements to Internet browsers may choose advertisements to display in a variety of ways. A website may simply have sponsors, and sell advertisements in an analogous manner to the sale of advertising space in a newspaper or magazine.
- However, some systems guess what may be appropriate or desirable for users based on limited available information. For example, contextual advertising systems may provide an advertisement for a web page based in part on a target word in the web page. These systems have no way of knowing if the advertisement is actually relevant to the user viewing the web page—the advertisement is chosen simply because it matches a target word on the web page. For example, Google may display advertisements based on words contained in a user's email message or search string. The advertisement is selected based on the content of the single email message being viewed. No other information about the user is available.
- Some systems decide what products may be desirable for a user based on ratings of other similar products provided by the user. For example, some recommendation services receive limited user ratings, or implicit ratings based on views or purchases, of a certain kind of product—books or movies for example—and recommend other books or movies that the user may like based on similarity to items favorably rated, such as authors, themes, actors, directors, genres, and the like.
- Similarly, other systems may select advertisements to display based on the content of stored cookies associated with the user browsing the website. This may be done in some cases without the user's informed consent, raising privacy concerns for the user.
- These previous systems also suffer from being proprietary to the particular website or electronic service accessed. For example, web sites such as Facebook, Ticketmaster, and ESPN, maintain some profile information associated with their users. However, the profile information stored by the user at one site is generally inaccessible to others, depriving the user of its benefit as they travel to other websites. Allowing one site to share information with others again raises privacy concerns. It often may be prohibitive for one system to obtain the necessary user consent to share profile information with another system.
- Accordingly, current systems have a variety of drawbacks in how they select and display advertisements.
-
FIG. 1 is a schematic diagram of a system according to an embodiment of the present invention. -
FIG. 2 is a schematic illustration of a conceptual database schema for an electronic profile according to an embodiment of the present invention. -
FIG. 3 is a schematic illustration of a profile management interface operating in a browser window of a display according to an embodiment of the present invention. -
FIG. 4 is a flowchart illustrating operation of a disambiguation engine according to an embodiment of the present invention. -
FIG. 5 is a flowchart illustrating operation of an indexing engine according to an embodiment of the present invention. -
FIG. 6 is a flowchart illustrating operation of a disambiguation engine according to an embodiment of the present invention. -
FIG. 7 is a flowchart illustrating operation of an analysis engine according to an embodiment of the present invention. -
FIG. 8 is a schematic illustration of a web browser operating a plug-in according to an embodiment of the present invention. -
FIG. 9 is a schematic illustration of a web browser operating a plug-in according to an embodiment of the present invention. -
FIG. 10 is a flowchart illustrating operation of a system according to an embodiment of the present invention. - Certain details are set forth below to provide a sufficient understanding of embodiments of the invention. However, it will be clear to one skilled in the art that embodiments of the invention may be practiced without various of these particular details. In some instances, well-known computer system components, network architectures, control signals, and software operations have not been shown in detail in order to avoid unnecessarily obscuring the described embodiments of the invention.
- Embodiments of the invention provide a system for selecting advertisements or other content for an entity accessing network accessible content. The selections are made by the system based on an electronic profile of the entity and the content accessed by the entity, such as, but not limited to, a web page, web site, email, messaging, message item, document, or image. A browser plug-in may render the selected advertisement, content, or both in a separate window or a portion of the browser window. In this manner, the selected content, advertisements, or both may remain as the entity browses to other sites or accesses other content. Although the same area may be used to display content and advertisements, the selected advertisements and content may change as the entity navigates to different websites or accesses different network accessible content.
- The electronic profiles used to select the content, advertisements, or both for display may have been developed by a profiling system, embodiments of which were described in concurrently filed, co-owned U.S. application Ser. No. ______, entitled “Electronic profile development, storage, use, and systems therefor,” filed Dec. 12, 2008, which application is hereby incorporated herein by reference in its entirety. Electronic profiles described herein include data structures containing information about an entity, all or a portion of which may be used as input to an analysis engine that selects contents, advertisements, or both, based in part on the electronic profile. As will be described below, an entity may control the use of all or portions of their electronic profile, allowing it to be used in part or completely to score and select content responsive to requests from particular entities. The analysis engine uses information from the electronic profile to select links to content, advertisements, or both, for the entity. The information contained in an electronic profile is generally information about an entity associated with the electronic profile, which may also be referred to as the entity owning the electronic profile. The entity may be a person or a group of people. The entity may also be a segment of people that share a common attribute. The entity may also be, but not limited to, a product, place, business, or item of content. The entity may be a segment of things that share a common attribute.
- An example of a
system 100 according to an embodiment of the present invention is shown inFIG. 1 . Aprofiling system 110 includes aprofile management system 115, adisambiguation engine 120, and ananalysis engine 125. These individual components will be discussed further below, and additional embodiments are described in concurrently filed, co-owned U.S. application Ser. No. ______, entitled “Electronic profile development, storage, use, and systems therefor,” filed Dec. 12, 2008, which application is hereby incorporated by reference in its entirety. Theprofiling system 110 generally includes a processor and memory to store computer readable instructions that may cause the processor to implement the functionalities of theprofile management system 115,disambiguation engine 120, andanalysis engine 125 described below. Although shown as a unitary system, theprofiling system 110 may be implemented as distributed across a plurality of computing devices, with portions of the processing performed by each of the devices. In embodiments of the present invention, theprofiling system 110 receives information about the web browsing activities of an entity, and enables the transmission of selected content to the entity, where the selected content is chosen based in part on an electronic profile associated with the entity and the information about the entity's web browsing activities. - A
user device 130, which may be implemented as generally any network connected, digital media delivery system or device. Theuser device 130 may have suitable processing, memory, and communication capabilities to implement acontent viewer 137, is in communication with theprofiling system 110. Theuser device 130 may also have the capability to implement aprofile management interface 135 in some embodiments, although in some embodiments theprofile management interface 135 may not be included on theuser device 130. Thecontent viewer 137 may be implemented as an Internet browser plug-in or as a stand-alone application used to view content selected based on information regarding an entity's browsing activity, network accessing activity, or both, and their electronic profile, as described further below, or thecontent viewer 137 may be embedded in a different application. Theuser device 130 may accordingly be, but is not limited to, a personal computer, kiosk, cell phone, personal digital assistant, television set-top box, television, GPS system, projector, display, or music player. Theuser device 130 may be specific to a single user, or may be used by multiple users, such as in the case of a publicly accessible workstation or kiosk. A display used by the entity as theuser device 130 may be co-located in a same physical device as a processor for performing functions of a user device described herein, or the display may be in a remote or different location than the display. That is, an entity may view content items, advertisements, or both, selected by a system according to embodiments of the present invention on a stand-alone display device that may have limited processing capability. In some embodiments, the stand-alone display device may be coupled to or in communication with a computing device having processing capability to perform the user device functionality described herein. In some embodiments, the user need not be a physical person, but may be a representative of a group of people, or may be another automated process or computer program performing a profile entry functionality. Communication between theprofiling system 110 and theuser device 130 may occur through any mechanism. In some embodiments, theprofiling system 110 may be implemented completely or partially as a web service that may communicate with theuser device 130 over the Internet using http, in either a secure or unsecured manner, as desired. Theprofile management interface 135 enables communication with theprofile management system 115 to establish, augment, or otherwise manipulate profile information pertaining to an entity represented by a user using theuser device 130. Thedisambiguation engine 120 may receive profile information supplied from theuser device 130 and further process the information to reduce ambiguity in the information provided, as will be described further below. The processing to reduce ambiguity may occur dynamically through interaction with the user device. Any number of user devices may be in communication with theprofiling system 110. - Profile information received from the
user device 130 and other sources is processed by theprofile management system 115 anddisambiguation engine 120 to generate electronic profiles that are stored in the electronic profile storage 140. As will be described further below, the electronic profiles may be database structures and accordingly may be stored in a database as shown inFIG. 1 . However, any type of electronic storage may be used to store electronic profiles and the profiles may be stored in any number of distinct storage locations, and individual profiles may be distributed across a plurality of storage locations. Electronic profiles will be discussed in greater detail below. - In embodiments of the present invention, the
profiling system 110 may receive further information from theuser device 130, such as a name or all or a portion of the content of a web page browsed by the entity operating theuser device 130. This information may also be stored in the electronic profile storage 140 or other storage, although it may only be temporarily stored, or may not be stored at all in some embodiments. - The
user device 130 further operates an Internet browser and acontent viewer 137, which may be a browser plug-in. In some embodiments the browser plug-in runs on thesame user device 130 as theprofile management interface 135, however in some embodiments thecontent viewer 137 operates on a user device having noprofile management interface 135. That is, an entity need not enter or refine profile information using the same device on which they will view advertisements and links selected based on their stored profile information. - The
user device 130 may be connected to a web server 139 or other sources of information over the Internet and an entity may use theuser device 130 to browse the web using any Internet browser or other software. -
Content sources 142 represent any source of content, including advertisements that may be images, text, video, or combinations thereof. Advertisements may be provided by any number of businesses or advertisers. Theanalysis engine 125, indexing engine, or combinations of engines, may analyze the content from thecontent sources 142 and store advertisements in thead storage 144 and links to content in thelink storage 146. In some embodiments,content sources 142,ad storage 144,link storage 146, or combinations thereof may include a set of content sources, advertisements, links, or combinations thereof that are designated as sponsored content sources, advertisements, or links. The sponsored content sources, advertisements, and links may be analyzed separately or differently from other content sources, advertisements, and links, and in some embodiments may be physically stored separately. Although shown as separate storage devices, in some embodiments the advertisements and content links may be stored on a same storage medium, and may be distributed across any number of physical storage locations. Further, in some embodiments the advertisements, links, or both may be stored on the same physical storage device as some or all of the electronic profiles in the electronic profile storage 140. As will be described further below, the advertisements and links may be stored along with an index indicating the relative frequency of terms in or associated with the advertisements and links. Although advertisements and links have been described other content, rich media, or other application functionalities may be stored an accessed by theprofiling system 110. - The
analysis engine 125 may score advertisements, links, rich media, other application functionality, or combinations thereof based on one or more of the electronic profiles stored in electronic profile storage 140. The score may additionally be influenced by a website accessed by theuser device 130. The output of this process may be provided to thecontent viewer 137 such that a number of relevant links, advertisements, or both are displayed in a browser window displayed on theuser device 130. There may be a fixed number of respective links and advertisements displayed, or all links or advertisements having a score above a certain threshold may be displayed in some embodiments. - Accordingly, an entity may communicate profile information to the
profiling system 110 through theprofile management interface 135 in communication with theprofile management system 115. Theprofile management system 115 and thedisambiguation engine 120 may refine and expand the profile information provided. An electronic profile of the entity is stored in electronic profile storage 140. While a single electronic profile storage 140 location is shown inFIG. 1 , the electronic profile may in some embodiments be distributed across a plurality of storage locations, including across a plurality of storage locations associated with different physical electronic devices that may be used by an entity. Accordingly, in some embodiments, only a portion of the entity's profile may be located on the electronic profile storage 140. As the entity browses the web or other network available content (either on theuser device 130 or another device), using a browser equipped with thecontent viewer 137, thecontent viewer 137 requests advertisements, links, or both from theanalysis engine 125. Thecontent viewer 137 may also transmit information about the network accessible content accessed to theprofiling system 110 for use by theanalysis engine 125. In embodiments where the network accessible content accessed includes a web page or web site, information about the webpage or site accessed may include but is not limited to URL, metadata, time and date visited, content of the website viewed, and website host. In embodiments where the network accessible content accessed is not a web page, the information transmitted may include metadata associated with the accessed content, terms or other features of the content, a location of the content, a file type, and one or more protocols associated with the content, or combinations thereof. - The
analysis engine 125 accesses the entity's electronic profile stored in electronic profile storage 140 and, provided the entity has chosen to allow all or a portion of its profile information to be used responsive to a request from thecontent viewer 137, scores thead storage 144,link storage 146, or both in accordance with the accessed electronic profile, information received about the website or page visited, or both. The resultant scores are used to select advertisement, links or both for display by thecontent viewer 137 in a browser on theuser device 130 along with the website content requested. - In this manner, the
profiling system 110 may serve as a trusted intermediary between an entity and advertisement and content provider. A content provider who provides content to be indexed and stored in thead storage 144,link storage 146, or both, will have that content communicated to users when theanalysis engine 125 determines that the content would be relevant for them. The content provider does not actually receive the profile information itself. Being able to control the accessibility of the profile information, and knowing content providers may not obtain the information directly, entities may share a greater amount of information with theprofiling system 110. - Further, through the
profile management system 115 anddisambiguation engine 120, the electronic profiles may be more structured while being easily created than those created purely through freeform user input. Thedisambiguation engine 120 may suggest related terms for addition to an entity's profile, that the entity may confirm or deny. - Having described an overview of an example of a
system 100 according to the present invention, examples of electronic profiles will now be discussed. Electronic profiles described herein include data structures containing information about an entity, all or a portion of which may be used as input to an analysis engine that may take a predictive or deterministic action based in part on the electronic profile. For example, recall electronic profiles may be stored in the electronic profile storage 140 and used by theanalysis engine 125 to identify advertisements or links to content that may be relevant to the entity associated with the electronic profile. - Examples of electronic profiles accordingly include data structures. Any type of data structure may be used that may store the electronic profile information described below. In one embodiment, the electronic profile is stored in a relational database.
FIG. 2 illustrates a portion of aconceptual database schema 200 for an electronic profile according to an embodiment of the present invention. Thedatabase schema 200 is organized as a star schema, but other organizations may be employed in other embodiments. Theschema 200 includes several tables relating aspects of the electronic profile to one another that provide information about the entity owning the electronic profile. The database constructed according to theschema 200 may be stored on generally any suitable electronic storage medium. In some embodiments, portions of an electronic profile may be distributed amongst several electronic storage media, including among storage media associated with different electronic devices used by an entity. - Information stored in an electronic profile about an entity may include, but is not limited to any combination of the following: data, preferences, possessions, social connections, images, permissions, recommendation preferences, location, role and context. These aspects of an entity may be used in any combination by an analysis engine to take predictive or deterministic action as generally described above. Examples of aspects of profile information included in the
electronic profile 200 will now be described further. - The electronic profile represented by the
schema 200 includes data about an entity in a user table 201. While the term ‘user’ is used inFIG. 2 to describe tables and other aspects of the profile, the term is not meant to restrict profiles to individuals or human representatives. The term ‘user’ inFIG. 2 simply refers to the entity associated with the profile. -
Data 202 about the entity stored in the user table 201. The table 201 may include a column for each type of data. For example, data associated with UserID1 includes name (‘Bob Smith’), address (555 Park Lane), age (35), and gender (Male) of the entity. Data associated with UserID2 includes height (5′10″), weight (180), and gender (Female). Data associated with UserID2 includes financial information and an address (329 Whistle Way). Data about an entity stored in the user table 201 may generally include factual or demographic information such as, but not limited to, height, address, clothing sizes, contact information, financial information, credit card number, ethnicity, weight, and gender. Any combination of data types may be stored. The user table 201 also includes auser ID 203. The user ID may be generated by a system generating or using the electronic profile, or may be associated with or identical to a user ID already owned by the profile owning entity, such as an email account or other existing account of the entity. Each entity having an electronic profile may have a corresponding user table, such as the user table 201, stored in the electronic profile storage 140 ofFIG. 1 . - Preferences of an entity may also be stored in the entity's electronic profile. Preferences generally refer to subjective associations between the entity and various words that may represent things, people, or groups. Each preference of an individual represents that association—“I like cats,” for example, may be one preference. Preferences may be stored in any suitable manner. In the schema of
FIG. 2 , preferences are stored by use of the user preferences table 210, the user preference terms table 220, the preference terms table 230, and the preference qualifiers table 240, which will be described further below. The four tables used to represent preference inFIG. 2 is exemplary only, and preferences may be stored in other ways in other embodiments such that a profile owning entity is associated with their preferences. - Referring again to
FIG. 2 , the user table 201 of an entity is associated with a user preferences table 210. The user preferences table 210 includesuserIDs 203 of entities having profiles in the electronic profile storage 140 and listsindividual preference IDs 211 associated with each userID. For example, the UserID1 is associated with SPORTS-PREFERENCE1 and SPORTS_TRAVEL_PREFERENCE1 in the example shown inFIG. 2 . Although shown as including only afew user IDs 203, the user preferences table 210 may generally include a list of multiple user IDs known to the profiling system and a list of individual preference IDs associated with the userIDs. In this manner, an entity's preferences may be associated with the data related to the entity. Generally, any string may be used to represent a preference ID. Also included in the user preference table 210 arequalifier IDs 212 that are used to record an association with terms contained in the preference. The qualifiers will be discussed further below. - Each preference ID has an associated entry in a user preference terms table 220. The user preference terms table 220 contains a list of term IDs associated with each user preference ID. In
FIG. 2 , for example, the preference ID SPORTS_PREFERENCE1 is shown associated with TermID1 and TermID2. Any string may generally be used to represent the term IDs. Each TermID in turn is associated with an entry in a preference term table 230. The preference term table 230 lists the actual terms represented by the TermID. A term may generally be any string and is generally a unit of meaning, which may be one or more words, or other representation. As shown inFIG. 2 , the preference terms table 230 indicates the TermID1 is associated with the term Major League Baseball. Although only one term is shown associated with the TermID1, any number of terms may be so associated. - Accordingly, as described above, an entity may be associated with preferences that ultimately contain one or more terms. However, the relationship between the entity and the terms has not yet been described. An entity's preferences may include a scale of likes, dislikes, or both of the entity. Further an entity's preferences may include information about what the entity is or is not, does or does not do in certain circumstances. In the
schema 200 ofFIG. 2 , each preference may be associated with one or more qualifiers, as indicated by an association between the preference ID and a qualifier ID in the user preferences table 210. A term associated with each qualifier ID is then stored in a preference qualifiers table 240. Qualifiers describe the relationship of the preference terms to the profile owning entity. Examples of qualifiers include ‘like’ and ‘dislike’ to describe a positive or negative association with a preference, respectively. Other qualifiers may be used including ‘when’, ‘when not’, ‘never’, ‘always’, ‘does’, ‘does not’, ‘is’, and ‘is not’ to make more complex associations between preference words and the profile owning entity. As shown inFIG. 2 , the qualifier QualID1 represents the association ‘like’ and, QualID2 represents the association ‘dislike’. - Accordingly, the structure shown in
FIG. 2 encodes two preferences for an entity represented by UserID1. SPORTS_PREFERENCE1 indicates UserID1 likes Major League Baseball and the Seattle Mariners. SPORTS_PREFERENCE2 indicates UserID1 likes Fenway Park. Similarly, UserID2 has SPORTS_PREFERENCE2, which indicates UserID2 dislikes Major League Baseball and the New York Yankees. UserID3 has SPORTS_PREFERENCE3, which indicates UserID3 likes Derek Jeter. - The manner of storing preferences using the tables described in
FIG. 2 may aid in efficient storage and analysis by allowing, for example, multiple termIDs to be associated with multiple user preference IDs without requiring storing the individual terms multiple times in the profile storage 140 ofFIG. 1 . Instead, multiple associations may be made between the termID and multiple user preferences. However, as discussed, generally, any data structure may be used to encode an electronic profile of an entity. In some embodiments, a profile may be represented and optionally stored as a vector or index. The vector may uniquely identify an entity associated with the profile. For example, the profile vector may represent a plurality of axes, each axis representing a term, word, or user device, and the vector include bits associated with each term, word, and user device to be included in the profile. - Further information regarding an entity may be stored in an entity's electronic profile including possessions, images, social connections, permissions, recommendation preferences, location, roles, context, and appearance settings for a content viewer. Although not shown in
FIG. 2 , these further aspects may be stored as additional star tables associated with the central user table 201. Possessions of the entity may include things the entity owns or has access to including, but not limited to, gaming systems, cell phones, computers, cars, clothes, bank or other accounts, subscriptions, and cable or other service providers. - Social connections of the entity may include, but are not limited to, connections to friends, family, neighbors, co-workers, organizations, membership programs, information about the entity's participation in social networks such as Facebook, Myspace, or LinkedIn, or businesses an entity is affiliated with.
- Permissions for accessing all or a portion of the electronic profile are described further below but may include an indication of when an entity's profile information may be used. For example, an entity may authorize their profile information to be used by the profiling system responsive only to requests from certain entities, and not responsive to requests from other entities. The permissions may specify when, how, how often, or where the profiling system may access the entity's profile responsive to a request from a specific entity, or type of entity. For example, an entity may specify that sports websites may obtain information about content relevant to the entity's profile, but that banks may not. As generally described above, only the profiling system has direct access to the stored profile information, and the profile information is not generally shared with content providers that may request scoring of their content based on the entity's profile. However, the scoring may only be undertaken in some embodiments when the entity has granted permission for their profile to be used to provide information to the particular content provider or browser plug-in.
- Recommendation preferences may include whether the entity would like or accept recommendations for additional information to be added to their electronic profile, or for data or possessions. The recommendation preferences may specify which entities may make recommendations for the electronic profile owning entity and under what conditions.
- Location information of the entity may include a current location determined in a variety of levels of granularity such as, but not limited to, GPS coordinate, country, state, city, region, store name, church, hotel, restaurant, airport, other venue, street address, or virtual location. In some embodiments location information may be obtained by analyzing an IP address associated with an entity.
- Roles of the entity may include categorizations of the entity's relationships to others or things including, but not limited to, father, mother, daughter, son, friend, worker, brother, sister, sports fan, movie fan, wholesaler, distributor, retailer, and virtual persona (such as in a gaming environment or other site).
- Context of the entity may include an indication of activities or modes of operation of the entity, including what the entity is doing in the past, present, or future, such as shopping, searching, working, driving, or processes the entity is engaged in such as purchasing a vacation.
- Appearance settings for a content viewer may also be stored in the electronic profile of an entity, which may include electronic wallpaper information, skinning, or branding information, or combinations thereof. The appearance settings may be used to render selected content for an entity in a window having the wallpaper, skin, or other appearance indicated by the appearance settings in an entity's electronic profile.
- As will be described further below, all or a portion of the electronic profile may be used as an input to an analysis engine. In some embodiments, there may be insufficient data about an individual to have a meaningful output of the analysis engine based on their electronic profile. Accordingly, in some embodiments the profile of a segment sharing one or more common attributes with the individual may be used as input to the analysis engine instead of or in addition to the individual's profile. The profile of a segment may also be used to select content that may be relevant for that segment of entities, and pass content to entities that share one or more attributes with the segment.
- Having described exemplary mechanisms for storing profile information and the content of electronic profiles, exemplary methods and systems for obtaining profile information will now be discussed. Profile information may generally be obtained from any source, including from a representative of the profile owning entity, other individuals, or from collecting data about the profile owning entity as they interact with other electronic systems. In some embodiments, referring back to
FIG. 1 , profile information may be directly entered by a profile owning entity or their representative from theuser device 130 using theprofile management interface 135. Profile information may be obtained generally at any time. In one embodiment, when an entity installs thecontent viewer 137, they may be prompted to establish an electronic profile. - The
profile management interface 135 may take any form suitable for receiving profile information from a profile owning entity or their representative. In one embodiment, theprofile management interface 135 includes an application operating on theuser device 130. The application on theuser device 130 may communicate with theprofiling system 110. In one embodiment, the disambiguation engine, analysis engine, or both may be implemented as an application programming interface (API), and the application operating on theuser device 130 may call one or more APIs operated by theprofiling system 110. In some embodiments, the application on theuser device 130 that is in communication with theprofiling system 110 operates in an Internet browser window, and one embodiment of theprofile management interface 135 is shown inFIG. 3 operating in a browser window of adisplay 305 of the user device. In other embodiments, an application runs on the user device, which may be any network connected, digital media delivery system or device, including a phone, personal computer, kiosk, cell phone, personal digital assistant, television set-top box, television, GPS system, projector, display, or music player, to interface with theprofiling system 110. A profile owning entity, or a representative of that entity, may enter profile information into thepreference entry field 310. Prior to entering information, the entity may have identified themselves to the profiling system by, for example, entering a username, password, or both, or other methods of authentication may be used including identification of one or more user devices and their context associated with the entity. When entering profile information into thepreference entry field 310, the entity may also select a qualifier associated with the profile information using aqualifier selector 308. Thequalifier selector 308, which may be unique for the entity in some embodiments, may include a drop-down menu, buttons depicting different qualifiers, or other mechanism. For example, thequalifier selector 308 may include a button for ‘Like’ and one for ‘Dislike’ so an entity could specify that they like or dislike the terms they provide in thepreference entry field 310. The entity may submit the entered profile information to theprofile management system 115 of theprofiling system 110 inFIG. 1 . Information may be submitted, for example, by pressing an enter key, or clicking on an enter button displayed in the browser window 302. The information may be communicated to theprofile management system 115 using any suitable communication protocol, including http. - Accordingly, profile owning entities may provide profile information to the
profile management system 115. The profile information may be directly captured—“I like cats” in the case of a preference, or “I am a father” in the case of a role. However, in some instances, the provided profile information may be ambiguous, such as “I like the giants.” It may be unclear whether the profile owning entity intends to indicate a preference for the New York Giants, the San Francisco Giants, or large people. - The profile information submitted by an entity may accordingly be submitted to the
disambiguation engine 120 ofFIG. 1 . As will be described further below, thedisambiguation engine 120 may provide a list of relevant terms that may be displayed in thedisambiguation selection area 320 ofFIG. 3 . An entity may then select the relevant terms from the disambiguation list for addition to the profile being managed. Alternatively or in addition, an entity may select or otherwise indicate, such as by right-clicking, one or more terms displayed anywhere in the browser window, or more generally displayed by the user device, that a term should be added to the entity's profile. Alternatively or in addition, embodiments of a profiling system may identify an action of the entity and automatically add a related term to the electronic profile of the entity. After processing by theanalysis engine 125, which will be described further below, relevant advertisements, links to relevant content, or both, may be displayed in thecontent area 330. In some embodiments, thecontent area 330 may not be provided on a same screen, or indeed on the same device, with theprofile management interface 135. That is, while profile information may be entered or revised on one device, content displayed or provided based on that profile information may be provided on a different device in some embodiments. - Accordingly, the
disambiguation engine 120 functions to select terms, based on preference information input by an entity, that may also be relevant to the entity and may be considered for addition to the entity's electronic profile. In one embodiment, thedisambiguation engine 120 may simply provide a list of all known terms containing the entity's input. For example, if the entity entered “giants,” a dictionary or sports listing of all phrases or teams containing the word “giants” may be provided. While this methodology may accurately capture additional profile information, it may be cumbersome to implement on a larger scale. - Accordingly, the
disambiguation engine 120 may function along with anindexing engine 420 as shown inFIG. 4 . Generally, theindexing engine 420 accesses one ormore content sources 410 to analyze the content stored in the accessedcontent sources 410 and generate an indexedcontent store 430. The content sources may include thecontent sources 142 ofFIG. 1 and in this manner theindexing engine 420 may generate the indexedad storage 144 andlink storage 146. Although shown as separate storage, the indexedcontent store 430 may include indexing information stored along with the content from thecontent sources 410, or may include only index records related to the content in the content sources 410. The index information generally includes information about the relative frequency of terms in the content from the content sources 410. In this manner, as will be described further below, terms may be identified that frequently appear along with a query term, or in a same pattern as a query table. Thedisambiguation engine 120 may then access the indexedcontent store 430 to more efficiently identify terms related to preferences expressed by an entity. The expressed preference may be stored in one storage location, or distributed across multiple storage locations. - The
indexing engine 420 may generally use any methodology to index documents from the content sources 410. Theindexing engine 420 generally includes a processor and memory encoded with computer readable instructions causing the processor to implement one or more of the functionalities described. The processor and memory may in some embodiments be shared with those used to implement the disambiguation engine, analysis engine, or combinations thereof. In one embodiment, a vector space representation of documents from thecontent sources 410 may be generated by theindexing engine 420. A vector representation of each document may be generated containing elements representing each term in the group of terms represented by all documents in thecontent sources 410 used. The vector may include a term frequency—inverse document frequency measurement for the term. An example of a method that may be executed by theindexing engine 420 is shown inFIG. 5 .FIG. 5 further demonstrates an example in which an indexedcontent store 430 may be created specific to a particular category. In some embodiments, however, the indexed content store may be generalized to one or more categories. However, in embodiments where the indexedcontent store 430 is specific to a single category of information, it may be advantageous to provide several content stores (which may be physically stored in the same or different media), each containing indexed content for a specific category. In this manner, the indexing performed by theindexing engine 420 will be specific to the category of information, and may in some cases enable greater relevance matching than querying a general content store. - Proceeding with reference to
FIG. 5 , the indexing engine may receive a list of categoryspecific expert content 512. The expert content may, for example, include a group of content in a particular category that may be considered representative of content in the category (using, for example, the Wikipedia Commons data set, or any other collection of information regarding a particular category). The indexing engine locates the category specific content in the list over the Internet or other digital source of category-specific content 510. The source of categoryspecific content 510 may be located in a single storage medium, or distributed among several storage mediums accessible to the indexing engine over the Internet or other communication mechanisms. - The indexing engine extracts the
text 514 from the expert content and may perform a variety of filtering procedures such as word normalization, dictionary look-up and commonEnglish term removal 516. During word normalization, tenses or variations of the same word are grouped together. During dictionary look-up, meanings of words can be extracted. During common English term removal, common words such as ‘and’ or ‘the’ may be removed and not further processed. Grammar, sentence structure, paragraph structure, and punctuation may also be discarded. The indexing engine may then perform vector space word-frequency decomposition 518 of the extracted text from each document. The use of the term document herein is not meant to limit the processing of actual text documents. Rather, the term document refers to each content unit accessed by the indexing engine, such as a computer file, and may have generally any length. - During the decomposition, each document may be rated based on the term frequency (TF) of the document. The term frequency describes the proportion of terms in the document that are unique. The term frequency may be calculated by the number of times the term appears in the document divided by the number of unique terms in the document. A vector of term frequencies may be generated by the indexing engine to describe each document, the vector having elements representing a term frequency for each term contained in the entire content store analyzed.
- The vector representing each document may also contain an inverse document frequency (IDF) measure, that reflects how often the term is used across all documents in the content score, and therefore a measure of how distinctive the term may be to specific documents. The IDF may be calculated as the log of the number of documents containing the term divided by the number of documents in the content store.
- In some embodiments, a Kullback-Leibler Divergence, DKL may also be included in a vector representation of a document. DKL may provide a measure of how close a document is to a query—generally, how much common information there is between the query and the document. DKL is a measure of a distance between two difference probability distributions—one representing the distribution of query terms, and the other representing the distribution of terms in the document. DKL may be calculated as:
-
- where p is the distribution of terms in the document, q is the distribution of query terms, and i represents each term. The distribution of terms in the document may be a vector with entries for each term in a content store, where the entries are weighted according to the frequency of each term in the document. The distribution of query terms may be a vector with entries for each term in a content store, where the entries are weighted according to the frequency of each term in the query.
- Accordingly, using TF-IDF, Kullback-Leibler Divergence, other methods of document relevance measurements, or combinations thereof, the indexed
content store 430 ofFIG. 4 contains one or more content indexes representing a measure of the importance of various terms to each analyzed document. - Having described the indexing of documents, a process for disambiguating a preference by the
disambiguation engine 120 using the indexedcontent store 430 is illustrated inFIG. 6 . An entity declares 610 a preference, for example by entry into thepreference entry field 310 ofFIG. 3 . Thedisambiguation engine 120 then selects anexpert content store 612 to query using the declared preference. The selection may be made in a variety of ways. In some embodiments, a single content store is used and no selection need be made. In other embodiments, thedisambiguation engine 120 receives contextual information about the entity entering preference information, and the contextual information is used to select the expert content store. For example, in one embodiment, the disambiguation engine receives information that the entity entering profile information is doing so from a sports-related website, and accordingly, an expert sports content store may be selected. - Documents in the expert content store are rated 614, as described above, based on their relevance to individual terms. In some embodiments, the rating is conducted once the preference is entered, while in others, the already stored vectors containing the measurements are accessed. A set of most relevant documents to the expressed preference may be identified. The most relevant documents may be identified by calculating a relevance number for each document based on the preference terms. A relevance number represents the relevancy of each document to the preference, using the entered preference terms. Embodiments of the relevance number use a 0-100 scale, and may accommodate a multi-term preference. The relevance number for a single term may generally be calculated as a normalized TF.IDF value. In one embodiment, the calculation may be made by subtracting a minimum TF.IDF value for all terms in the indexed content store from the TF.IDF value of the term and dividing the result by the difference between the maximum TF.IDF value for all terms in the indexed content store in the minimum TF.IDF value for all terms in the indexed content store. For multiple terms in a preference, the relevance number of each document may be given as:
-
- NTerms is the number of terms in the query. The relevance number accordingly is a sum of the relevance numbers for each term in the query, divided by the number of terms. The Kullback-Leibler Divergence, DKL, may also be used as a relevance number to score content items from a content store, or across multiple content stores. In the case of DKL, a lower DKL number indicates a more relevant content item (as it may indicate the information space between the item and the preference is small).
- While in some embodiments, the calculation of relevance numbers may not change over time as the profiling system operates, in some embodiments relevance numbers or the method for calculating relevance numbers, may be modified in a variety of ways as the profiling system operates. The relevance numbers may be modified through entity feedback or other learning methodologies including neural networks. For example, relevance numbers as calculated above may be used to develop a set of neural network weights that may be used to initialize a neural network that may refine and learn techniques for generating or modifying relevance values. The neural network may be trained on a set of training cases, that may be developed in any of a variety of ways, including by using entity selection of a document to set a target value of a resultant relevance number. During training, or during operation of the profiling system, error functions may be generated between a desired outcome (such as a training case where an entity or administrator specifies the relevance score, or a situation in operation where entity feedback indicates a particular relevance score) and a calculated relevance number. The error function may be used to modify the neural network or other system or method used to calculate the relevance number. In this manner, the computation of relevance numbers, and in some embodiments, the relevance numbers themselves, may change as the profiling system interacts with content items and entities. For example, a relevance value for a content item may be increased if entity feedback indicates the content item is of greater or lesser relevance. The entity feedback may be explicit, such as indicating a degree of relevance the entity would assign to the content item, or implicit, such as by identifying multiple entities have selected the content item or responded to the content item to a degree that indicates the relevance number should be higher, or lower, than that assigned by the profiling system. Entity feedback may also include feedback obtained by monitoring the activity, selections, or both of one or more entities without necessarily receiving intentional feedback from the entity. Examples of neural networks, entity feedback modification, and other computer learning techniques usable with embodiments of the present invention are described in co-pending U.S. Provisional Application ______, entitled “Determining relevant information for domains of interest,” filed Dec. 12, 2008, which application is hereby incorporated by reference in its entirety for any purpose.
- Referring back to
FIG. 6 , the set of significantly relevant documents may be identified by setting a threshold relevance number, or by setting a fixed number of results, and selecting that number of results in relevance number order, regardless of the absolute value of the relevance number. In some embodiments, the most relevant documents are selected by identifying a place in a relevance-ranked list of documents where a significant change in relevance score occurs between consecutive results. So, if, for example, there are documents with relevance numbers of 90, 89, 87, 85, 82, 80, 60, 59, 58 . . . then a threshold relevance number of 80 may be selected because it occurs prior to the relatively larger twenty-point relevance drop to the next document. - After the most relevant documents have been selected, the disambiguation engine may determine the most distinctive related
key words 616 in those documents. The most relevant keywords may be determined by weighting the highest TF.IDF terms in the documents by the relevance number of the document in which they appear, and taking a sum of that product over all the documents for each term. The terms having results over a threshold, or a fixed number of highest resulting terms, may be selected by the disambiguation engine as most distinctiverelated keywords 616. These selected keywords may be presented to the entity to determine if the keyword is useful 620. For example, the keywords may be listed in thedisambiguation selection area 320 ofFIG. 3 . The preference entering entity may find that one or more of the identified keywords helps to refine the preference they have entered, or for other reasons should be included in their electronic profile, and may indicate the keyword should be added 622 to their preference. The disambiguation engine may further continue the disambiguation operation by repeating the process shown inFIG. 6 using the added preference terms. If keywords are not identified as belonging to an entity's preference, the declared preference is stored 624. - Accordingly, examples of the entry of profile information and refinement of entered profile information have been described above that may facilitate the creation and storage of electronic profiles. Referring back to
FIG. 1 , the information contained in an entity's electronic profile may be used by theanalysis engine 125 to take a predictive or deterministic action. A variety of predictive or deterministic actions may be taken by theanalysis engine 125 based in part on information contained in an entity's electronic profile. Products, things, locations, or services may be selected and suggested, described, or presented to an entity based on information contained in the entity's electronic profile. In other embodiments, other entities may be notified of a possible connection to or interest in an entity based on their electronic profile. Content on a website browsed by an entity may be modified in accordance with their profile in some embodiments. Theprofiling system 110 may also generate or assist in the provider device generating a notification, alert, email, message, or other correspondence for the entity based on its profile. Accordingly, the analysis engine may take action for the entity or for third parties based on the entity's profile information. In one embodiment, which will be described further below, theanalysis engine 125 selects content for presentation to the entity based on their electronic profile. - An example of operation of the
analysis engine 125 to select relevant advertisements, links, or both, for an entity is shown inFIG. 7 . Theanalysis engine 125 receivesinformation 711 about a network accessible content item, such as but not limited to, a website, web page, email, messaging, message item, document, or image, accessed by an entity, or simply receives a request for information from a browser plug-in being operated by the entity or on its behalf. Theanalysis engine 125 accesses 710 a stored preference in an entity's electronic profile. In some embodiments, a single stored preference is accessed, in some embodiments selected preferences may be accessed, and in some embodiments all stored preferences may be accessed. The selection of which preferences associated with an entity to access may in some embodiments be made according to the context of the request for analysis. For example, if the request comes from a sports content provider, one or more sports-related preferences may be accessed. In other embodiments, multiple preferences may be accessed and the context of the request or of the entity may alter the manner in which the relevance number is computed. For example, in some embodiments a total relevance number is calculated by summing individual relevance numbers calculated using a respective preference. A weighted sum may also be taken, with the weight accorded to each individual relevance number based on the preference with which it is associated. Accordingly, an entity's context, which may be stored in the entity's electronic profile, may determine the weighting of individual preferences in calculating a relevance number. - A specific request may not be required to begin the process shown in
FIG. 7 . Theanalysis engine 125 may select 712 one or more content indices for analysis based on a context in which theanalysis 125 is operating. In some embodiments, the content index or indices to use may already be known, or there may only be one, in which case theselection 712 may not be necessary. For example, theanalysis engine 125 may utilize the ad andlink storage FIG. 1 . - Referring back to
FIG. 7 , the analysis engine scores 714 content in the selected indices based on the accessed preferences and received information about the network accessible content item(s), such as website(s) or web pages, accessed. The scoring process may occur in any manner, including a manner that allows the analysis engine to evaluate content items based on terms in the stored preference. In one embodiment, the scoring process includes assigning a relevance number to content items based on terms in the preference and terms received about the website as described above with reference toFIG. 6 and thedocument rating 614 performed during preference disambiguation. However, in this case, the content items are simply scored and further analysis of relevant terms within the document may not be done, as was done during preference disambiguation. - Accordingly, content items in the selected indices are scored by calculating a reference number using the term(s) in the accessed electronic profile preference and term(s) received about the network accessible content items, such as web site(s) or page(s) accessed. Relevant advertisements and content links may then be selected 716 in a similar manner to the selection of documents and terms for the disambiguation of preferences described above. That is, content may be selected having a relevance number over a threshold, or a fixed number of highest rated content items may be selected, or all content items preceding a sharp decline in relevance number may be selected. The selected links, advertisements, or both may then be displayed in the
content area 330 of the user device display shown inFIG. 3 . - Having described an overview of selecting relevant advertisements and links to relevant content using electronic profile information associated with an entity as well as information about one or more network accessible content items, such as websites or web pages, visited by the entity, an example of how the
content viewer 137 may display those relevant advertisement(s), link(s), or both will now be described with reference toFIG. 8 . Of course, the relevant content may be displayed differently in other embodiments. - A
browser window 820 is shown inFIG. 8 . The browser window may be generated by any Internet browser program including but not limited to Internet Explorer, Mozilla, Safari, and Firefox. Additionally, the Internet browser program may be operating on any type of user device as generally described above. Thebrowser window 820 generally displayswebsite content 802 of websites visited by an entity. As is generally understood, as the entity browses the web, and follows links or enters URLs, different website content will be displayed in thearea 802. Thecontent viewer 137 described above with reference toFIG. 1 may render arelevant content area 804. Therelevant content area 804 may overlay portions of thewebsite content 802, and may generally be positioned by a viewer to a suitable location in thebrowser window 820, and may be pinned down as known in the art in any desired location. However, in one embodiment, as shown inFIG. 8 , therelevant content area 804 makes use of unused screen width 810 that may be present when a widescreen monitor is used. Large or widescreen displays, such as displays wider than about 1024 pixels, although in some embodiments larger than 800×600 pixels, and in some embodiments wider than 1000 pixels, may have unused screen width 810 when rendering a typical website. In the process of installing a viewer, such as thecontent viewer 137, the application may assess a screen resolution of theuser device 130 and make a determination regarding where on the screen to position the viewer. The application may recommend that the entity utilize a different monitor if the experience would be non-optimal. The typical website may be designed to appear on a screen having a different aspect ratio or width, and the unused space 810 may be present when a screen of a widescreen aspect ratio is used. In some embodiments, thecontent viewer 137 is configured to render the links, advertisements, or both, selected by theanalysis engine 125 in the unused space 810. In this manner, the items displayed in therelevant content area 804 may not affect the display ofwebpage content 802. In other embodiments, thecontent viewer 137 may render therelevant content area 804 within thewebsite content area 802. In some embodiments, an entity viewing therelevant content area 804 may select the position of thearea 804 in the display of the user device by dragging thearea 804 around and clicking to place it in a fixed location. - The
content viewer 137 may also facilitate reporting to advertisers or other content providers, provided an entity has configured their electronic profile such that it may be used to provide such information. Theprofiling system 110 may track a number of advertisement impressions delivered over a specified time period, and thecontent viewer 137 may report click-throughs on advertisements or content links to theprofiling system 110. In this manner, the profiling system can report ad impressions and click through rates. Theprofiling system 110 may also aggregate consumer profile data based on the electronic profiles of entities that have viewed the advertisements, clicked on the advertisements, or both. In some embodiments, theprofiling system 110 aggregates data only when an entity's electronic profile indicates it may be so used. Reporting of click through or other data may be performed using standards employed by the Internet Advertising Bureau or other organizations. Click throughs may be reported related to advertisements, content, or both. Further, reporting may include information regarding what other advertisements, content, or both were displayed to the entity. Still further, in some embodiments, reporting can include information provided to theprofiling system 110 to make the selection of the advertisements and links provided to the entity. - The
relevant content area 804 may include the relevant links, advertisements, rich media, applications, or combinations thereof, supplied by theanalysis engine 125. In the embodiment ofFIG. 8 , five links and one advertisement are provided. The links are displayed above the advertisement inFIG. 8 , although other configurations are possible. As the viewer browses the web and visits different web pages, the content displayed in thewebsite content area 802 may change. As the new website information is transmitted to theanalysis engine 125, the links and ads displayed in therelevant content area 804 may also change. Although shown inFIG. 8 as a web browser window, therelevant content area 804 may in other applications be a separate application or process and, instead of or in addition to displaying selections based on a web page or site viewed, display selections based on other network accessible content accessed by an entity, such as but not limited to documents, imagery, and correspondence such as emails. A viewer may click on the links or ads in therelevant content area 804, causing further information related to the selection to appear in thewebpage content area 802. In some embodiments, an entity may add information to their electronic profile by selecting terms appearing in thewebpage content area 802 or therelevant content area 804 and right-clicking or otherwise indicating that the selected term should be transmitted to theprofiling system 110 for inclusion in the entity's electronic profile. - In this manner, an entity operating a user device may completely control information displayed in an application window. The content displayed is based on the entity's profile and network accessible content accessed by the entity. In this manner, advertisements, content, rich media, applications, and combinations thereof, may be more accurately targeted to the entity.
- An example scenario for use of the
content viewer 137 andanalysis engine 125 will now be described with reference toFIG. 10 . Thecontent viewer 137 is initiated 1005. This may occur, for example by starting up an Internet browser on the user device that is equipped with a browser plug-in including software to perform the user device functions described. In some embodiments, a separate application is started up on the user device that performs the functions of thecontent viewer 137. Once launched, thecontent viewer 137 may display an initial content set. The initial content may be a default selection of advertisements, links, rich media, or combinations thereof. In other embodiments, the initial content may be selected based on the electronic profile of the entity. In such an embodiment, the identity of the entity operating thecontent viewer 137 is transmitted 1010 to theanalysis engine 125. The entity may be identified in substantially any manner, including by logging into thecontent viewer 137 with a username, password, or both, or by transmitting an identification of theuser device 130 to theanalysis engine 125. Having received an indication of the identity of the entity, theanalysis engine 125 may access 1015 the stored electronic profile associated with the entity. The initial content may be selected 1020 based on the electronic profile of the entity, in some embodiments in combination with known past browsing history of the entity, which may also be stored in the entity's electronic profile. The initial content viewer display may be rendered 1025 using appearance settings stored in the entity's electronic profile, such as by displaying a wallpaper, skin, or brand stored in the entity's electronic profile. In this manner, the initial information displayed by thecontent viewer 137 may be a default setting, or selected based on the entity's profile, past browsing history, or both. - The entity then browses 1030 to a web page using an Internet browser or similar viewer, or in other embodiments the entity accessed any type of network accessible content in any manner. Information about the web page visited, or content accessed, by the entity is transmitted 1035 to the
analysis engine 125. The information, as described above, may include metadata associated with the web page, a URL, content of the web page, or combinations thereof. In embodiments where the network accessible content accessed is not a web page, the information transmitted may include metadata associated with the accessed content, terms or other features of the content, a location of the content, a file type, and one or more protocols associated with the content, or combinations thereof. Theanalysis engine 125 selects 1040 content based on the entity's electronic profile and the web page information received. The selected content is then displayed 1045 by thecontent viewer 137. In this manner, as an entity browses to different web pages, or accesses different network accessible content, the displayed content in thecontent viewer 137 may change accordingly. - From the foregoing it will be appreciated that, although specific embodiments of the invention have been described herein for purposes of illustration, various modifications may be made without deviating from the spirit and scope of the invention.
Claims (26)
Priority Applications (11)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US12/334,416 US20090216639A1 (en) | 2008-02-25 | 2008-12-12 | Advertising selection and display based on electronic profile information |
EP09714387A EP2260408A2 (en) | 2008-02-25 | 2009-02-25 | Electronic profile development, storage, use and systems for taking action based thereon |
EP20130166494 EP2624153A1 (en) | 2008-02-25 | 2009-02-25 | Electronic profile development, storage, use and systems for taking action based thereon |
CA2716432A CA2716432C (en) | 2008-02-25 | 2009-02-25 | Electronic profile development, storage, use and systems for taking action based thereon |
CN200980114379.6A CN102067119B (en) | 2008-02-25 | 2009-02-25 | Electronic profile development, storage, use and the system of taking action based on it |
JP2010547868A JP5429498B2 (en) | 2008-02-25 | 2009-02-25 | A system for developing, storing, using, and taking actions based on electronic profiles |
EP20130166481 EP2624151A1 (en) | 2008-02-25 | 2009-02-25 | Electronic profile development, storage, use and systems for taking action based thereon |
EP20110150913 EP2354982A1 (en) | 2008-02-25 | 2009-02-25 | Electronic profile development, storage, use and systems for taking action based thereon |
EP20130166675 EP2626798A1 (en) | 2008-02-25 | 2009-02-25 | Electronic profile development, storage, use and systems for taking action based thereon |
EP20130166490 EP2624152A1 (en) | 2008-02-25 | 2009-02-25 | Electronic profile development, storage, use and systems for taking action based thereon |
PCT/US2009/035197 WO2009108732A2 (en) | 2008-02-25 | 2009-02-25 | Electronic profile development, storage, use and systems for taking action based thereon |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US6716208P | 2008-02-25 | 2008-02-25 | |
US12/334,416 US20090216639A1 (en) | 2008-02-25 | 2008-12-12 | Advertising selection and display based on electronic profile information |
Publications (1)
Publication Number | Publication Date |
---|---|
US20090216639A1 true US20090216639A1 (en) | 2009-08-27 |
Family
ID=40512368
Family Applications (5)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US12/334,416 Abandoned US20090216639A1 (en) | 2008-02-25 | 2008-12-12 | Advertising selection and display based on electronic profile information |
US12/334,389 Expired - Fee Related US8255396B2 (en) | 2008-02-25 | 2008-12-12 | Electronic profile development, storage, use, and systems therefor |
US12/392,900 Expired - Fee Related US8402081B2 (en) | 2008-02-25 | 2009-02-25 | Platform for data aggregation, communication, rule evaluation, and combinations thereof, using templated auto-generation |
US13/560,214 Abandoned US20130138512A1 (en) | 2008-02-25 | 2012-07-27 | Electronic profile development, storage, use, and systems therefor |
US13/762,138 Abandoned US20130151570A1 (en) | 2008-02-25 | 2013-02-07 | Platform for data aggregation, communication, rule evaluation, and combinations thereof, using templated auto-generation |
Family Applications After (4)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US12/334,389 Expired - Fee Related US8255396B2 (en) | 2008-02-25 | 2008-12-12 | Electronic profile development, storage, use, and systems therefor |
US12/392,900 Expired - Fee Related US8402081B2 (en) | 2008-02-25 | 2009-02-25 | Platform for data aggregation, communication, rule evaluation, and combinations thereof, using templated auto-generation |
US13/560,214 Abandoned US20130138512A1 (en) | 2008-02-25 | 2012-07-27 | Electronic profile development, storage, use, and systems therefor |
US13/762,138 Abandoned US20130151570A1 (en) | 2008-02-25 | 2013-02-07 | Platform for data aggregation, communication, rule evaluation, and combinations thereof, using templated auto-generation |
Country Status (6)
Country | Link |
---|---|
US (5) | US20090216639A1 (en) |
EP (7) | EP2354982A1 (en) |
JP (1) | JP5429498B2 (en) |
CN (1) | CN102067119B (en) |
CA (2) | CA2716432C (en) |
WO (2) | WO2009108724A2 (en) |
Cited By (72)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20090216563A1 (en) * | 2008-02-25 | 2009-08-27 | Michael Sandoval | Electronic profile development, storage, use and systems for taking action based thereon |
US20090216750A1 (en) * | 2008-02-25 | 2009-08-27 | Michael Sandoval | Electronic profile development, storage, use, and systems therefor |
US20110154266A1 (en) * | 2009-12-17 | 2011-06-23 | Microsoft Corporation | Camera navigation for presentations |
WO2011151718A1 (en) * | 2010-06-04 | 2011-12-08 | Sean Grant Riley | Online advertising system and a method of operating the same |
US20120095827A1 (en) * | 1998-12-29 | 2012-04-19 | Vora Sanjay V | Structured web advertising |
US20120173991A1 (en) * | 2010-12-31 | 2012-07-05 | Verizon Patent And Licensing, Inc. | Media Content User Interface Systems and Methods |
US20120173327A1 (en) * | 2011-01-03 | 2012-07-05 | International Business Machines Corporation | Promoting, delivering and selling information to intranet users |
US20120324043A1 (en) * | 2011-06-14 | 2012-12-20 | Google Inc. | Access to network content |
US20130006897A1 (en) * | 2011-07-01 | 2013-01-03 | Google Inc. | Predicting user navigation events |
US20130031459A1 (en) * | 2011-07-27 | 2013-01-31 | Behrooz Khorashadi | Web browsing enhanced by cloud computing |
US20130046623A1 (en) * | 2011-08-17 | 2013-02-21 | Telefonaktiebolaget L M Ericsson (Publ) | Method For Providing a Recommendation, Recommender System, and Recommender Computer Program Product |
US20130066711A1 (en) * | 2011-09-09 | 2013-03-14 | c/o Facebook, Inc. | Understanding Effects of a Communication Propagated Through a Social Networking System |
WO2013078532A1 (en) * | 2011-12-02 | 2013-06-06 | Research In Motion Limited | Methods and devices for configuring a web browser based on an other party's profile |
US20130254642A1 (en) * | 2012-03-20 | 2013-09-26 | Samsung Electronics Co., Ltd. | System and method for managing browsing histories of web browser |
US8566696B1 (en) | 2011-07-14 | 2013-10-22 | Google Inc. | Predicting user navigation events |
US8600921B2 (en) | 2011-09-15 | 2013-12-03 | Google Inc. | Predicting user navigation events in a browser using directed graphs |
US8655819B1 (en) | 2011-09-15 | 2014-02-18 | Google Inc. | Predicting user navigation events based on chronological history data |
US8661327B1 (en) * | 2011-01-06 | 2014-02-25 | Intuit Inc. | Method and system for automated insertion of relevant hyperlinks into social media-based communications |
US8732569B2 (en) | 2011-05-04 | 2014-05-20 | Google Inc. | Predicting user navigation events |
US8745212B2 (en) | 2011-07-01 | 2014-06-03 | Google Inc. | Access to network content |
US8744988B1 (en) | 2011-07-15 | 2014-06-03 | Google Inc. | Predicting user navigation events in an internet browser |
US8793235B2 (en) | 2012-01-19 | 2014-07-29 | Google Inc. | System and method for improving access to search results |
US8843518B2 (en) * | 2012-07-17 | 2014-09-23 | Verizon Patent And Licensing Inc. | Method and apparatus for establishing a connection with known individuals |
US8880566B2 (en) | 2005-10-26 | 2014-11-04 | Cortica, Ltd. | Assembler and method thereof for generating a complex signature of an input multimedia data element |
US8887239B1 (en) | 2012-08-08 | 2014-11-11 | Google Inc. | Access to network content |
US8984647B2 (en) | 2010-05-06 | 2015-03-17 | Atigeo Llc | Systems, methods, and computer readable media for security in profile utilizing systems |
US20150095150A1 (en) * | 2013-09-30 | 2015-04-02 | The Toronto-Dominion Bank | Systems and methods for administering investment portfolios based on transaction data |
US20150095132A1 (en) * | 2013-09-30 | 2015-04-02 | The Toronto-Dominion Bank | Systems and methods for administering investment portfolios based on information consumption |
US9053431B1 (en) | 2010-10-26 | 2015-06-09 | Michael Lamport Commons | Intelligent control with hierarchical stacked neural networks |
US9104664B1 (en) | 2011-10-07 | 2015-08-11 | Google Inc. | Access to search results |
US9141722B2 (en) | 2012-10-02 | 2015-09-22 | Google Inc. | Access to network content |
US9191626B2 (en) | 2005-10-26 | 2015-11-17 | Cortica, Ltd. | System and methods thereof for visual analysis of an image on a web-page and matching an advertisement thereto |
US9218606B2 (en) | 2005-10-26 | 2015-12-22 | Cortica, Ltd. | System and method for brand monitoring and trend analysis based on deep-content-classification |
US9235557B2 (en) | 2005-10-26 | 2016-01-12 | Cortica, Ltd. | System and method thereof for dynamically associating a link to an information resource with a multimedia content displayed in a web-page |
US20160048884A1 (en) * | 2012-09-27 | 2016-02-18 | Livingsocial, Inc. | Client-based deal filtering and display |
US9286623B2 (en) | 2005-10-26 | 2016-03-15 | Cortica, Ltd. | Method for determining an area within a multimedia content element over which an advertisement can be displayed |
EP3007125A1 (en) * | 2014-10-08 | 2016-04-13 | Sears Brands, LLC | Member profiles and associated systems, methods, and media |
US9330189B2 (en) | 2005-10-26 | 2016-05-03 | Cortica, Ltd. | System and method for capturing a multimedia content item by a mobile device and matching sequentially relevant content to the multimedia content item |
US9374411B1 (en) * | 2013-03-21 | 2016-06-21 | Amazon Technologies, Inc. | Content recommendations using deep data |
US9396435B2 (en) | 2005-10-26 | 2016-07-19 | Cortica, Ltd. | System and method for identification of deviations from periodic behavior patterns in multimedia content |
US9430439B2 (en) | 2011-09-09 | 2016-08-30 | Facebook, Inc. | Visualizing reach of posted content in a social networking system |
US9466068B2 (en) | 2005-10-26 | 2016-10-11 | Cortica, Ltd. | System and method for determining a pupillary response to a multimedia data element |
US9489431B2 (en) | 2005-10-26 | 2016-11-08 | Cortica, Ltd. | System and method for distributed search-by-content |
US20160378847A1 (en) * | 2015-06-26 | 2016-12-29 | Sri International | Distributional alignment of sets |
US9558449B2 (en) | 2005-10-26 | 2017-01-31 | Cortica, Ltd. | System and method for identifying a target area in a multimedia content element |
US9584579B2 (en) | 2011-12-01 | 2017-02-28 | Google Inc. | Method and system for providing page visibility information |
US9639532B2 (en) | 2005-10-26 | 2017-05-02 | Cortica, Ltd. | Context-based analysis of multimedia content items using signatures of multimedia elements and matching concepts |
US9646006B2 (en) | 2005-10-26 | 2017-05-09 | Cortica, Ltd. | System and method for capturing a multimedia content item by a mobile device and matching sequentially relevant content to the multimedia content item |
US9646005B2 (en) | 2005-10-26 | 2017-05-09 | Cortica, Ltd. | System and method for creating a database of multimedia content elements assigned to users |
US9747420B2 (en) | 2005-10-26 | 2017-08-29 | Cortica, Ltd. | System and method for diagnosing a patient based on an analysis of multimedia content |
US9769285B2 (en) | 2011-06-14 | 2017-09-19 | Google Inc. | Access to network content |
US9875440B1 (en) | 2010-10-26 | 2018-01-23 | Michael Lamport Commons | Intelligent control with hierarchical stacked neural networks |
US9946792B2 (en) | 2012-05-15 | 2018-04-17 | Google Llc | Access to network content |
US10223742B2 (en) * | 2015-08-26 | 2019-03-05 | Google Llc | Systems and methods for selecting third party content based on feedback |
US10380623B2 (en) | 2005-10-26 | 2019-08-13 | Cortica, Ltd. | System and method for generating an advertisement effectiveness performance score |
US10387914B2 (en) | 2005-10-26 | 2019-08-20 | Cortica, Ltd. | Method for identification of multimedia content elements and adding advertising content respective thereof |
US10607355B2 (en) | 2005-10-26 | 2020-03-31 | Cortica, Ltd. | Method and system for determining the dimensions of an object shown in a multimedia content item |
US10733326B2 (en) | 2006-10-26 | 2020-08-04 | Cortica Ltd. | System and method for identification of inappropriate multimedia content |
US10742340B2 (en) | 2005-10-26 | 2020-08-11 | Cortica Ltd. | System and method for identifying the context of multimedia content elements displayed in a web-page and providing contextual filters respective thereto |
US10848590B2 (en) | 2005-10-26 | 2020-11-24 | Cortica Ltd | System and method for determining a contextual insight and providing recommendations based thereon |
US10949773B2 (en) | 2005-10-26 | 2021-03-16 | Cortica, Ltd. | System and methods thereof for recommending tags for multimedia content elements based on context |
US11019161B2 (en) | 2005-10-26 | 2021-05-25 | Cortica, Ltd. | System and method for profiling users interest based on multimedia content analysis |
US11032017B2 (en) | 2005-10-26 | 2021-06-08 | Cortica, Ltd. | System and method for identifying the context of multimedia content elements |
US20210397658A1 (en) * | 2011-03-14 | 2021-12-23 | Newsplug, Inc. | Systems and Methods for Enabling a User to Operate on Displayed Web Content via a Web Browser Plug-In |
US11216498B2 (en) | 2005-10-26 | 2022-01-04 | Cortica, Ltd. | System and method for generating signatures to three-dimensional multimedia data elements |
US11232489B2 (en) | 2017-04-24 | 2022-01-25 | Consumer Direct, Inc. | Scenario gamification to provide actionable elements and temporally appropriate advertising |
US11386139B2 (en) | 2005-10-26 | 2022-07-12 | Cortica Ltd. | System and method for generating analytics for entities depicted in multimedia content |
US11386175B2 (en) * | 2017-09-28 | 2022-07-12 | Sharp Kabushiki Kaisha | Content recommendation apparatus, method of content recommendation, and content recommendation system |
US11514517B2 (en) | 2017-04-24 | 2022-11-29 | Consumer Direct, Inc. | Scenario gamification to provide improved mortgage and securitization |
US11604847B2 (en) | 2005-10-26 | 2023-03-14 | Cortica Ltd. | System and method for overlaying content on a multimedia content element based on user interest |
US11620327B2 (en) | 2005-10-26 | 2023-04-04 | Cortica Ltd | System and method for determining a contextual insight and generating an interface with recommendations based thereon |
US11853371B1 (en) * | 2018-07-31 | 2023-12-26 | Meta Platforms, Inc. | Logging information describing a type of event occurring in a mobile application received via an SDK incorporated into mobile application code of the mobile application |
Families Citing this family (87)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP2260373A4 (en) * | 2008-02-25 | 2016-08-03 | Atigeo Llc | Determining relevant information for domains of interest |
US8171031B2 (en) * | 2008-06-27 | 2012-05-01 | Microsoft Corporation | Index optimization for ranking using a linear model |
US8161036B2 (en) * | 2008-06-27 | 2012-04-17 | Microsoft Corporation | Index optimization for ranking using a linear model |
US8832676B2 (en) * | 2009-09-30 | 2014-09-09 | Zynga Inc. | Apparatuses, methods and systems for a social networking application updater |
US20110119312A1 (en) * | 2009-11-15 | 2011-05-19 | Arjun Chopra | System and method for automated scalability of n-tier computer applications |
US8843465B2 (en) | 2010-01-29 | 2014-09-23 | Google Inc. | Distributing content |
EP2398210B1 (en) * | 2010-06-17 | 2016-11-16 | Huawei Technologies Co., Ltd. | Targeted mobile advertising via user proxy at femto AP |
TW201205307A (en) | 2010-07-30 | 2012-02-01 | Ibm | Method, apparatus and computer program product for efficiently sharing information |
US10216393B2 (en) | 2010-07-30 | 2019-02-26 | International Business Machines Corporation | Efficiently sharing user selected information with a set of determined recipients |
US8555332B2 (en) | 2010-08-20 | 2013-10-08 | At&T Intellectual Property I, L.P. | System for establishing communications with a mobile device server |
US8438285B2 (en) | 2010-09-15 | 2013-05-07 | At&T Intellectual Property I, L.P. | System for managing resources accessible to a mobile device server |
US8516039B2 (en) * | 2010-10-01 | 2013-08-20 | At&T Intellectual Property I, L.P. | Apparatus and method for managing mobile device servers |
US8989055B2 (en) | 2011-07-17 | 2015-03-24 | At&T Intellectual Property I, L.P. | Processing messages with a device server operating in a telephone |
US8504449B2 (en) | 2010-10-01 | 2013-08-06 | At&T Intellectual Property I, L.P. | Apparatus and method for managing software applications of a mobile device server |
US9392316B2 (en) | 2010-10-28 | 2016-07-12 | At&T Intellectual Property I, L.P. | Messaging abstraction in a mobile device server |
MX2013006108A (en) * | 2010-11-29 | 2013-10-01 | Jingit Llc | Engagement and payment processing platform. |
US9066123B2 (en) | 2010-11-30 | 2015-06-23 | At&T Intellectual Property I, L.P. | System for monetizing resources accessible to a mobile device server |
US20120174038A1 (en) * | 2011-01-05 | 2012-07-05 | Disney Enterprises, Inc. | System and method enabling content navigation and selection using an interactive virtual sphere |
US20120233250A1 (en) * | 2011-03-11 | 2012-09-13 | International Business Machines Corporation | Auto-updatable document parts within content management systems |
US9342280B2 (en) | 2011-05-27 | 2016-05-17 | Microsoft Technology Licesning, LLC | Travel log for manipulation of content |
US20130031076A1 (en) * | 2011-07-28 | 2013-01-31 | Kikin, Inc. | Systems and methods for contextual searching of semantic entities |
US8849819B2 (en) * | 2011-08-05 | 2014-09-30 | Deacon Johnson | System and method for controlling and organizing metadata associated with on-line content |
US8782117B2 (en) * | 2011-08-24 | 2014-07-15 | Microsoft Corporation | Calling functions within a deterministic calling convention |
US10789526B2 (en) | 2012-03-09 | 2020-09-29 | Nara Logics, Inc. | Method, system, and non-transitory computer-readable medium for constructing and applying synaptic networks |
US10467677B2 (en) | 2011-09-28 | 2019-11-05 | Nara Logics, Inc. | Systems and methods for providing recommendations based on collaborative and/or content-based nodal interrelationships |
US11151617B2 (en) | 2012-03-09 | 2021-10-19 | Nara Logics, Inc. | Systems and methods for providing recommendations based on collaborative and/or content-based nodal interrelationships |
US8170971B1 (en) | 2011-09-28 | 2012-05-01 | Ava, Inc. | Systems and methods for providing recommendations based on collaborative and/or content-based nodal interrelationships |
US11727249B2 (en) | 2011-09-28 | 2023-08-15 | Nara Logics, Inc. | Methods for constructing and applying synaptic networks |
US8732101B1 (en) | 2013-03-15 | 2014-05-20 | Nara Logics, Inc. | Apparatus and method for providing harmonized recommendations based on an integrated user profile |
JP5814772B2 (en) * | 2011-12-15 | 2015-11-17 | ヤフー株式会社 | Advertisement determination system, advertisement determination method and program |
AU2013213683B2 (en) * | 2012-03-10 | 2013-11-07 | Evado Holdings Pty Ltd | A method and system of application development for multiple device client platforms |
US8935368B2 (en) * | 2012-04-16 | 2015-01-13 | International Business Machines Corporation | Data collection from networked devices |
CN103581111B (en) * | 2012-07-20 | 2017-12-12 | 腾讯科技(深圳)有限公司 | A kind of communication means and system |
US20140047319A1 (en) * | 2012-08-13 | 2014-02-13 | Sap Ag | Context injection and extraction in xml documents based on common sparse templates |
US20140078054A1 (en) * | 2012-09-14 | 2014-03-20 | Dan Zacharias GÄRDENFORS | Display control device and system |
US10215434B2 (en) | 2012-11-07 | 2019-02-26 | Think Automatic, LLC | Adaptive trigger sequencing for site control automation |
WO2014124318A1 (en) * | 2013-02-08 | 2014-08-14 | Interdigital Patent Holdings, Inc. | METHOD AND APPARATUS FOR INCORPORATING AN INTERNET OF THINGS (IoT) SERVICE INTERFACE PROTOCOL LAYER IN A NODE |
CN104021124B (en) * | 2013-02-28 | 2017-11-03 | 国际商业机器公司 | Methods, devices and systems for handling web data |
US10380105B2 (en) | 2013-06-06 | 2019-08-13 | International Business Machines Corporation | QA based on context aware, real-time information from mobile devices |
WO2015064072A1 (en) | 2013-10-30 | 2015-05-07 | パナソニックIpマネジメント株式会社 | Information provision system, specific-information generation device, and specific-information generation method |
CN104679753B (en) * | 2013-11-26 | 2019-02-26 | 腾讯科技(深圳)有限公司 | A kind of method for pushing and device of message |
US10162877B1 (en) * | 2013-12-17 | 2018-12-25 | VCE IP Holding Company LLC | Automated compilation of content |
US20150215257A1 (en) * | 2014-01-26 | 2015-07-30 | Linda Allan Mosquera | Customizing communications |
US10789300B2 (en) | 2014-04-28 | 2020-09-29 | Red Hat, Inc. | Method and system for providing security in a data federation system |
GB2527323B (en) * | 2014-06-18 | 2016-06-15 | Ibm | Runtime protection of web services |
US10104049B2 (en) * | 2014-09-12 | 2018-10-16 | Vmware, Inc. | Secure distributed publish/subscribe system |
CN104376406B (en) * | 2014-11-05 | 2019-04-16 | 上海计算机软件技术开发中心 | A kind of enterprise innovation resource management and analysis method based on big data |
US11126598B1 (en) * | 2014-11-06 | 2021-09-21 | Ab Initio Technology Llc | Techniques for performing lifecycle operations on a data store |
FR3030079A1 (en) * | 2014-12-10 | 2016-06-17 | Univ De Toulon | MEANS FOR DETERMINING A LEVEL OF RELEVANCE OF A RESOURCE IN AN INFORMATION PROCESSING SYSTEM |
WO2016183563A1 (en) | 2015-05-14 | 2016-11-17 | Walleye Software, LLC | Historical data replay utilizing a computer system |
EP3314903B1 (en) * | 2015-06-26 | 2021-03-17 | British Telecommunications public limited company | Digital content provision |
US9864598B2 (en) | 2015-09-18 | 2018-01-09 | ReactiveCore LLC | System and method for providing supplemental functionalities to a computer program |
US9552200B1 (en) | 2015-09-18 | 2017-01-24 | ReactiveCore LLC | System and method for providing supplemental functionalities to a computer program via an ontology instance |
US11157260B2 (en) | 2015-09-18 | 2021-10-26 | ReactiveCore LLC | Efficient information storage and retrieval using subgraphs |
US9335991B1 (en) | 2015-09-18 | 2016-05-10 | ReactiveCore LLC | System and method for providing supplemental functionalities to a computer program via an ontology instance |
US9372684B1 (en) | 2015-09-18 | 2016-06-21 | ReactiveCore LLC | System and method for providing supplemental functionalities to a computer program via an ontology instance |
US11276006B2 (en) | 2015-10-02 | 2022-03-15 | Outlier AI, Inc. | System, apparatus, and method to identify intelligence using a data processing platform |
CN108140044A (en) * | 2015-10-07 | 2018-06-08 | 皇家飞利浦有限公司 | For determining the equipment, system and method with the relevant information of clinician |
WO2017088010A1 (en) * | 2015-11-23 | 2017-06-01 | Lucell Pty Ltd (Acn 78 609 013 185) | Value assessment and alignment device, method and system |
US10411946B2 (en) * | 2016-06-14 | 2019-09-10 | TUPL, Inc. | Fixed line resource management |
US10231076B1 (en) | 2016-09-16 | 2019-03-12 | Wells Fargo Bank, N.A. | Systems and methods for providing contextual recommendations |
CN106709232A (en) * | 2016-11-09 | 2017-05-24 | 洛阳晶云信息科技有限公司 | Display method used for electronic medical record system, data entry method used for electronic medical record system, and medical record template revision method used for electronic medical record system |
US10257128B2 (en) * | 2016-11-28 | 2019-04-09 | Microsoft Technology Licensing, Llc | Presenting messages to participants based on neighborhoods |
US10152356B2 (en) | 2016-12-07 | 2018-12-11 | Vmware, Inc. | Methods and apparatus for limiting data transferred over the network by interpreting part of the data as a metaproperty |
US10552180B2 (en) | 2016-12-07 | 2020-02-04 | Vmware, Inc. | Methods, systems, and apparatus to trigger a workflow in a cloud computing environment |
US11481239B2 (en) | 2016-12-07 | 2022-10-25 | Vmware, Inc. | Apparatus and methods to incorporate external system to approve deployment provisioning |
EP3555842A1 (en) * | 2017-01-13 | 2019-10-23 | Huawei Technologies Co., Ltd. | Aggregation platform, requirement owner, and methods thereof |
JP2018156149A (en) * | 2017-03-15 | 2018-10-04 | オムロン株式会社 | Medication supporting device, method and program |
US20180276704A1 (en) * | 2017-03-27 | 2018-09-27 | Jpmorgan Chase Bank, N.A. | Systems and methods for using internet service co-branded financial instruments |
US11321402B2 (en) * | 2017-05-05 | 2022-05-03 | Microsoft Technology Licensing, Llc. | Index storage across heterogenous storage devices |
US10002154B1 (en) | 2017-08-24 | 2018-06-19 | Illumon Llc | Computer data system data source having an update propagation graph with feedback cyclicality |
KR102486236B1 (en) * | 2017-12-26 | 2023-01-09 | 삼성전자주식회사 | Apparatus and method for network function virtualization in wireless communication system |
FR3083949B1 (en) * | 2018-07-16 | 2021-08-06 | Ismart | PROCESS FOR RELIABILITY OF A COMMUNICATION BETWEEN AT LEAST ONE REMOTE SERVER AND ONE SERVER, BY AUTOMATIC MATCHING OF REFERENCE DATA |
US11823041B1 (en) * | 2018-08-30 | 2023-11-21 | Alarm.Com Incorporated | Extending learning of artificial intelligent systems |
US11533387B2 (en) * | 2018-11-30 | 2022-12-20 | Cerner Innovation, Inc. | Interface engine architecture |
AU2020100309B4 (en) * | 2019-03-20 | 2020-09-24 | Parametric Systems Pty Ltd | Techniques for Controlling Interaction with an Application Database |
CN109903143A (en) * | 2019-03-27 | 2019-06-18 | 深圳市活力天汇科技股份有限公司 | A kind of flight recommended method based on customer consumption level |
US11010442B2 (en) | 2019-09-06 | 2021-05-18 | Outlier AI, Inc. | Systems and methods for intelligence delivery |
US10719374B1 (en) * | 2019-09-17 | 2020-07-21 | Capital One Services, Llc | Application programming interface generator using database metadata |
US11243979B1 (en) * | 2019-11-26 | 2022-02-08 | Amazon Technologies, Inc. | Asynchronous propagation of database events |
US11449407B2 (en) | 2020-05-28 | 2022-09-20 | Bank Of America Corporation | System and method for monitoring computing platform parameters and dynamically generating and deploying monitoring packages |
US20220051322A1 (en) * | 2020-08-17 | 2022-02-17 | Bonaire Software Solutions, Llc | System and method for creating and managing a data attribute condition trigger matrix |
US11704168B2 (en) * | 2021-04-14 | 2023-07-18 | Adobe Inc. | Templates for mapping data events to API calls |
US11861425B2 (en) * | 2021-05-19 | 2024-01-02 | Red Hat, Inc. | Runtime mapping of asynchronous application programming interface messaging topics and schemas |
US11741093B1 (en) | 2021-07-21 | 2023-08-29 | T-Mobile Usa, Inc. | Intermediate communication layer to translate a request between a user of a database and the database |
KR102369960B1 (en) * | 2021-07-30 | 2022-03-04 | 쿠팡 주식회사 | Electronic apparatus for providing information based on existence of a user account and method thereof |
JP7418877B1 (en) | 2023-03-13 | 2024-01-22 | 株式会社テクロス | information processing equipment |
Citations (66)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5794210A (en) * | 1995-12-11 | 1998-08-11 | Cybergold, Inc. | Attention brokerage |
US6385602B1 (en) * | 1998-11-03 | 2002-05-07 | E-Centives, Inc. | Presentation of search results using dynamic categorization |
US6408290B1 (en) * | 1997-12-04 | 2002-06-18 | Microsoft Corporation | Mixtures of bayesian networks with decision graphs |
US6434556B1 (en) * | 1999-04-16 | 2002-08-13 | Board Of Trustees Of The University Of Illinois | Visualization of Internet search information |
US20020129014A1 (en) * | 2001-01-10 | 2002-09-12 | Kim Brian S. | Systems and methods of retrieving relevant information |
US6453347B1 (en) * | 1999-10-29 | 2002-09-17 | Mcafee.Com, Inc. | Active marketing based on client computer configurations |
US20020184401A1 (en) * | 2000-10-20 | 2002-12-05 | Kadel Richard William | Extensible information system |
US6560590B1 (en) * | 2000-02-14 | 2003-05-06 | Kana Software, Inc. | Method and apparatus for multiple tiered matching of natural language queries to positions in a text corpus |
US6581072B1 (en) * | 2000-05-18 | 2003-06-17 | Rakesh Mathur | Techniques for identifying and accessing information of interest to a user in a network environment without compromising the user's privacy |
US20030154129A1 (en) * | 2002-02-12 | 2003-08-14 | Capital One Financial Corporation | Methods and systems for marketing comparable products |
US20030204496A1 (en) * | 2002-04-29 | 2003-10-30 | X-Mine, Inc. | Inter-term relevance analysis for large libraries |
US20030229507A1 (en) * | 2001-07-13 | 2003-12-11 | Damir Perge | System and method for matching donors and charities |
US20040128508A1 (en) * | 2001-08-06 | 2004-07-01 | Wheeler Lynn Henry | Method and apparatus for access authentication entity |
US20040158569A1 (en) * | 2002-11-15 | 2004-08-12 | Evans David A. | Method and apparatus for document filtering using ensemble filters |
US20050043989A1 (en) * | 2003-08-19 | 2005-02-24 | Shifrin Daniel G. | System and method of facilitating content delivery to a user |
US20050076060A1 (en) * | 2003-10-06 | 2005-04-07 | Cemer Innovation, Inc. | System and method for creating a visualization indicating relationships and relevance to an entity |
US20050216434A1 (en) * | 2004-03-29 | 2005-09-29 | Haveliwala Taher H | Variable personalization of search results in a search engine |
US20050222989A1 (en) * | 2003-09-30 | 2005-10-06 | Taher Haveliwala | Results based personalization of advertisements in a search engine |
US6961731B2 (en) * | 2000-11-15 | 2005-11-01 | Kooltorch, L.L.C. | Apparatus and method for organizing and/or presenting data |
US20050257400A1 (en) * | 1998-11-06 | 2005-11-24 | Microsoft Corporation | Navigating a resource browser session |
US20060122994A1 (en) * | 2004-12-06 | 2006-06-08 | Yahoo! Inc. | Automatic generation of taxonomies for categorizing queries and search query processing using taxonomies |
US20060195515A1 (en) * | 2005-02-28 | 2006-08-31 | Yahoo! Inc. | System and method for rating media |
US7149733B2 (en) * | 2002-07-20 | 2006-12-12 | Microsoft Corporation | Translation of object queries involving inheritence |
US20060294084A1 (en) * | 2005-06-28 | 2006-12-28 | Patel Jayendu S | Methods and apparatus for a statistical system for targeting advertisements |
US20070038765A1 (en) * | 2002-02-27 | 2007-02-15 | Microsoft Corporation | User-centric consent management system and method |
US20070038608A1 (en) * | 2005-08-10 | 2007-02-15 | Anjun Chen | Computer search system for improved web page ranking and presentation |
US7191182B2 (en) * | 2002-07-20 | 2007-03-13 | Microsoft Corporation | Containment hierarchy in a database system |
US20070100898A1 (en) * | 2000-02-10 | 2007-05-03 | Involve Technology, Inc. | System for Creating and Maintaining a Database of Information Utilizing User Opinions |
US20070106659A1 (en) * | 2005-03-18 | 2007-05-10 | Yunshan Lu | Search engine that applies feedback from users to improve search results |
US20070130109A1 (en) * | 2005-12-05 | 2007-06-07 | Raymond King | Metadata collection within a trusted relationship to increase search relevance |
US20070136371A1 (en) * | 2005-12-12 | 2007-06-14 | Mci, Inc. | Profile-based user access to a network management system |
US7237245B2 (en) * | 1999-02-23 | 2007-06-26 | Microsoft Corporation | Object connectivity through loosely coupled publish and subscribe events |
US20070162443A1 (en) * | 2006-01-12 | 2007-07-12 | Shixia Liu | Visual method and apparatus for enhancing search result navigation |
US20070168546A1 (en) * | 2006-01-18 | 2007-07-19 | Microsoft Corporation | Efficient Dispatch of Messages Based on Message Headers |
US7257817B2 (en) * | 2001-10-16 | 2007-08-14 | Microsoft Corporation | Virtual network with adaptive dispatcher |
US20070225995A1 (en) * | 2006-03-17 | 2007-09-27 | Moore Barrett H | Method and Security Modules for an Incident Deployment and Response System for Facilitating Access to Private Civil Security Resources |
US7296022B2 (en) * | 2003-07-14 | 2007-11-13 | Microsoft Corporation | Method and system for accessing a network database as a web service |
US20070266019A1 (en) * | 2004-06-24 | 2007-11-15 | Lavi Amir | System for facilitating search over a network |
US20080009268A1 (en) * | 2005-09-14 | 2008-01-10 | Jorey Ramer | Authorized mobile content search results |
US20080040219A1 (en) * | 2006-08-09 | 2008-02-14 | Jeff Kim | Proximity-based wireless advertising system |
US20080046313A1 (en) * | 2006-08-17 | 2008-02-21 | Shuwei Chen | Methods and apparatus for serving relevant advertisements using web browser bars |
US20080104048A1 (en) * | 2006-09-15 | 2008-05-01 | Microsoft Corporation | Tracking Storylines Around a Query |
US20080134086A1 (en) * | 2006-12-01 | 2008-06-05 | Institute For Information Industry | User interface apparatus, method, and computer readable medium thereof |
US20080140521A1 (en) * | 2006-12-12 | 2008-06-12 | Sivakumar Jambunathan | Dynamic Modification Of Advertisements Displayed In Response To A Search Engine Query |
US20080162537A1 (en) * | 2006-12-29 | 2008-07-03 | Ebay Inc. | Method and system for utilizing profiles |
US20080263022A1 (en) * | 2007-04-19 | 2008-10-23 | Blueshift Innovations, Inc. | System and method for searching and displaying text-based information contained within documents on a database |
US20080300986A1 (en) * | 2007-06-01 | 2008-12-04 | Nhn Corporation | Method and system for contextual advertisement |
US20090063473A1 (en) * | 2007-08-31 | 2009-03-05 | Powerset, Inc. | Indexing role hierarchies for words in a search index |
US20090070412A1 (en) * | 2007-06-12 | 2009-03-12 | D Angelo Adam | Providing Personalized Platform Application Content |
US20090094093A1 (en) * | 2007-10-05 | 2009-04-09 | Yahoo! Inc. | System for selecting advertisements |
US20090106324A1 (en) * | 2007-10-19 | 2009-04-23 | Oracle International Corporation | Push-model based index deletion |
US20090171697A1 (en) * | 2005-11-29 | 2009-07-02 | Glauser Tracy A | Optimization and Individualization of Medication Selection and Dosing |
US20090216563A1 (en) * | 2008-02-25 | 2009-08-27 | Michael Sandoval | Electronic profile development, storage, use and systems for taking action based thereon |
US20090216750A1 (en) * | 2008-02-25 | 2009-08-27 | Michael Sandoval | Electronic profile development, storage, use, and systems therefor |
US20090216696A1 (en) * | 2008-02-25 | 2009-08-27 | Downs Oliver B | Determining relevant information for domains of interest |
US20090287683A1 (en) * | 2008-05-14 | 2009-11-19 | Bennett James D | Network server employing client favorites information and profiling |
US7627599B2 (en) * | 2005-05-20 | 2009-12-01 | Palo Alto Research Center Incorporated | Method, apparatus, and program product for visualizing tree structured information |
US20090327327A1 (en) * | 2008-06-26 | 2009-12-31 | Sailesh Sathish | Method, apparatus and computer program product for providing context triggered distribution of context models |
US20090327259A1 (en) * | 2005-04-27 | 2009-12-31 | The University Of Queensland | Automatic concept clustering |
US7644098B2 (en) * | 2007-04-24 | 2010-01-05 | Yahoo! Inc. | System and method for identifying advertisements responsive to historical user queries |
US20100153324A1 (en) * | 2008-12-12 | 2010-06-17 | Downs Oliver B | Providing recommendations using information determined for domains of interest |
US7779004B1 (en) * | 2006-02-22 | 2010-08-17 | Qurio Holdings, Inc. | Methods, systems, and products for characterizing target systems |
US20100228715A1 (en) * | 2003-09-30 | 2010-09-09 | Lawrence Stephen R | Personalization of Web Search Results Using Term, Category, and Link-Based User Profiles |
US20100328312A1 (en) * | 2006-10-20 | 2010-12-30 | Justin Donaldson | Personal music recommendation mapping |
US20110276563A1 (en) * | 2010-05-06 | 2011-11-10 | Michael Sandoval | Systems, methods, and computer readable media for security in profile utilizing systems |
US20140189107A1 (en) * | 2007-11-27 | 2014-07-03 | Zettics, Inc. | System and method for sharing anonymous user profiles with a third party |
Family Cites Families (26)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR940001563B1 (en) * | 1985-01-21 | 1994-02-24 | 가부시끼가이샤 히다찌세이사꾸쇼 | Rule base system |
US5873076A (en) * | 1995-09-15 | 1999-02-16 | Infonautics Corporation | Architecture for processing search queries, retrieving documents identified thereby, and method for using same |
JPH10222540A (en) * | 1996-12-04 | 1998-08-21 | N T T Data Tsushin Kk | Document retrieving method, device and recording medium |
DE19901908A1 (en) * | 1999-01-19 | 1999-09-23 | Joachim Zuckarelli | Method for visualizing search results for search queries with two linked search concepts |
US6587876B1 (en) * | 1999-08-24 | 2003-07-01 | Hewlett-Packard Development Company | Grouping targets of management policies |
US7734680B1 (en) * | 1999-09-30 | 2010-06-08 | Koninklijke Philips Electronics N.V. | Method and apparatus for realizing personalized information from multiple information sources |
US7020867B2 (en) * | 2001-03-23 | 2006-03-28 | S2 Technologies, Inc. | System and method for automatically generating code templates for communication via a predefined communication interface |
JP2002318820A (en) * | 2001-04-19 | 2002-10-31 | Aloka Co Ltd | Medical treatment information providing system |
US6968551B2 (en) * | 2001-06-11 | 2005-11-22 | John Hediger | System and user interface for generation and processing of software application installation instructions |
US20020198943A1 (en) * | 2001-06-20 | 2002-12-26 | David Zhuang | Web-enabled two-way remote messaging facility |
US7133862B2 (en) * | 2001-08-13 | 2006-11-07 | Xerox Corporation | System with user directed enrichment and import/export control |
JP2003256318A (en) * | 2002-02-27 | 2003-09-12 | Nec Corp | System, method, and program for distributing advertisement |
CA2513490A1 (en) | 2003-01-24 | 2004-08-05 | Gery Michel Ducatel | Searching apparatus and methods |
JP2004348241A (en) * | 2003-05-20 | 2004-12-09 | Hitachi Ltd | Information providing method, server, and program |
US7490286B2 (en) * | 2003-09-25 | 2009-02-10 | International Business Machines Corporation | Help option enhancement for interactive voice response systems |
US20060106793A1 (en) * | 2003-12-29 | 2006-05-18 | Ping Liang | Internet and computer information retrieval and mining with intelligent conceptual filtering, visualization and automation |
US20050223368A1 (en) * | 2004-03-30 | 2005-10-06 | Tonic Solutions, Inc. | Instrumented application for transaction tracing |
US7827176B2 (en) * | 2004-06-30 | 2010-11-02 | Google Inc. | Methods and systems for endorsing local search results |
WO2006037054A1 (en) * | 2004-09-27 | 2006-04-06 | Browster, Inc. | Method and apparatus for enhanced browsing |
US7516122B2 (en) * | 2004-12-02 | 2009-04-07 | Computer Associates Think, Inc. | System and method for implementing a management component that exposes attributes |
US20060277248A1 (en) * | 2005-05-12 | 2006-12-07 | Baxter Eugene E | Configuration-based application architecture using XML/XSLT |
US7984058B2 (en) * | 2005-06-02 | 2011-07-19 | Genius.Com Incorporated | Database query construction and handling |
US8140529B2 (en) * | 2005-07-28 | 2012-03-20 | International Business Machines Corporation | Method and apparatus for autonomically regulating information transfer when accessing database resources |
US20070198328A1 (en) * | 2006-02-09 | 2007-08-23 | Fuller William T | Storage Capacity Planning |
US8769407B2 (en) * | 2007-07-31 | 2014-07-01 | International Business Machines Corporation | Pointing help system |
US9311402B2 (en) | 2007-12-21 | 2016-04-12 | Semantinet Ltd. | System and method for invoking functionalities using contextual relations |
-
2008
- 2008-12-12 US US12/334,416 patent/US20090216639A1/en not_active Abandoned
- 2008-12-12 US US12/334,389 patent/US8255396B2/en not_active Expired - Fee Related
-
2009
- 2009-02-25 EP EP20110150913 patent/EP2354982A1/en not_active Ceased
- 2009-02-25 EP EP09714387A patent/EP2260408A2/en not_active Withdrawn
- 2009-02-25 JP JP2010547868A patent/JP5429498B2/en not_active Expired - Fee Related
- 2009-02-25 WO PCT/US2009/035181 patent/WO2009108724A2/en active Application Filing
- 2009-02-25 EP EP09714729A patent/EP2260409A1/en not_active Withdrawn
- 2009-02-25 WO PCT/US2009/035197 patent/WO2009108732A2/en active Application Filing
- 2009-02-25 CN CN200980114379.6A patent/CN102067119B/en not_active Expired - Fee Related
- 2009-02-25 EP EP20130166675 patent/EP2626798A1/en not_active Withdrawn
- 2009-02-25 EP EP20130166481 patent/EP2624151A1/en not_active Withdrawn
- 2009-02-25 CA CA2716432A patent/CA2716432C/en not_active Expired - Fee Related
- 2009-02-25 EP EP20130166490 patent/EP2624152A1/en not_active Withdrawn
- 2009-02-25 EP EP20130166494 patent/EP2624153A1/en not_active Withdrawn
- 2009-02-25 US US12/392,900 patent/US8402081B2/en not_active Expired - Fee Related
- 2009-02-25 CA CA2805391A patent/CA2805391C/en not_active Expired - Fee Related
-
2012
- 2012-07-27 US US13/560,214 patent/US20130138512A1/en not_active Abandoned
-
2013
- 2013-02-07 US US13/762,138 patent/US20130151570A1/en not_active Abandoned
Patent Citations (67)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5794210A (en) * | 1995-12-11 | 1998-08-11 | Cybergold, Inc. | Attention brokerage |
US6408290B1 (en) * | 1997-12-04 | 2002-06-18 | Microsoft Corporation | Mixtures of bayesian networks with decision graphs |
US6385602B1 (en) * | 1998-11-03 | 2002-05-07 | E-Centives, Inc. | Presentation of search results using dynamic categorization |
US20050257400A1 (en) * | 1998-11-06 | 2005-11-24 | Microsoft Corporation | Navigating a resource browser session |
US7237245B2 (en) * | 1999-02-23 | 2007-06-26 | Microsoft Corporation | Object connectivity through loosely coupled publish and subscribe events |
US6434556B1 (en) * | 1999-04-16 | 2002-08-13 | Board Of Trustees Of The University Of Illinois | Visualization of Internet search information |
US6453347B1 (en) * | 1999-10-29 | 2002-09-17 | Mcafee.Com, Inc. | Active marketing based on client computer configurations |
US20070100898A1 (en) * | 2000-02-10 | 2007-05-03 | Involve Technology, Inc. | System for Creating and Maintaining a Database of Information Utilizing User Opinions |
US6560590B1 (en) * | 2000-02-14 | 2003-05-06 | Kana Software, Inc. | Method and apparatus for multiple tiered matching of natural language queries to positions in a text corpus |
US6581072B1 (en) * | 2000-05-18 | 2003-06-17 | Rakesh Mathur | Techniques for identifying and accessing information of interest to a user in a network environment without compromising the user's privacy |
US20020184401A1 (en) * | 2000-10-20 | 2002-12-05 | Kadel Richard William | Extensible information system |
US6961731B2 (en) * | 2000-11-15 | 2005-11-01 | Kooltorch, L.L.C. | Apparatus and method for organizing and/or presenting data |
US20020129014A1 (en) * | 2001-01-10 | 2002-09-12 | Kim Brian S. | Systems and methods of retrieving relevant information |
US20030229507A1 (en) * | 2001-07-13 | 2003-12-11 | Damir Perge | System and method for matching donors and charities |
US20040128508A1 (en) * | 2001-08-06 | 2004-07-01 | Wheeler Lynn Henry | Method and apparatus for access authentication entity |
US7257817B2 (en) * | 2001-10-16 | 2007-08-14 | Microsoft Corporation | Virtual network with adaptive dispatcher |
US20030154129A1 (en) * | 2002-02-12 | 2003-08-14 | Capital One Financial Corporation | Methods and systems for marketing comparable products |
US20070038765A1 (en) * | 2002-02-27 | 2007-02-15 | Microsoft Corporation | User-centric consent management system and method |
US20030204496A1 (en) * | 2002-04-29 | 2003-10-30 | X-Mine, Inc. | Inter-term relevance analysis for large libraries |
US7149733B2 (en) * | 2002-07-20 | 2006-12-12 | Microsoft Corporation | Translation of object queries involving inheritence |
US7191182B2 (en) * | 2002-07-20 | 2007-03-13 | Microsoft Corporation | Containment hierarchy in a database system |
US20040158569A1 (en) * | 2002-11-15 | 2004-08-12 | Evans David A. | Method and apparatus for document filtering using ensemble filters |
US7296022B2 (en) * | 2003-07-14 | 2007-11-13 | Microsoft Corporation | Method and system for accessing a network database as a web service |
US20050043989A1 (en) * | 2003-08-19 | 2005-02-24 | Shifrin Daniel G. | System and method of facilitating content delivery to a user |
US20050222989A1 (en) * | 2003-09-30 | 2005-10-06 | Taher Haveliwala | Results based personalization of advertisements in a search engine |
US20100228715A1 (en) * | 2003-09-30 | 2010-09-09 | Lawrence Stephen R | Personalization of Web Search Results Using Term, Category, and Link-Based User Profiles |
US20050076060A1 (en) * | 2003-10-06 | 2005-04-07 | Cemer Innovation, Inc. | System and method for creating a visualization indicating relationships and relevance to an entity |
US20050216434A1 (en) * | 2004-03-29 | 2005-09-29 | Haveliwala Taher H | Variable personalization of search results in a search engine |
US20070266019A1 (en) * | 2004-06-24 | 2007-11-15 | Lavi Amir | System for facilitating search over a network |
US20060122994A1 (en) * | 2004-12-06 | 2006-06-08 | Yahoo! Inc. | Automatic generation of taxonomies for categorizing queries and search query processing using taxonomies |
US20060195515A1 (en) * | 2005-02-28 | 2006-08-31 | Yahoo! Inc. | System and method for rating media |
US20070106659A1 (en) * | 2005-03-18 | 2007-05-10 | Yunshan Lu | Search engine that applies feedback from users to improve search results |
US20090327259A1 (en) * | 2005-04-27 | 2009-12-31 | The University Of Queensland | Automatic concept clustering |
US7627599B2 (en) * | 2005-05-20 | 2009-12-01 | Palo Alto Research Center Incorporated | Method, apparatus, and program product for visualizing tree structured information |
US20060294084A1 (en) * | 2005-06-28 | 2006-12-28 | Patel Jayendu S | Methods and apparatus for a statistical system for targeting advertisements |
US20070038608A1 (en) * | 2005-08-10 | 2007-02-15 | Anjun Chen | Computer search system for improved web page ranking and presentation |
US20080009268A1 (en) * | 2005-09-14 | 2008-01-10 | Jorey Ramer | Authorized mobile content search results |
US20090171697A1 (en) * | 2005-11-29 | 2009-07-02 | Glauser Tracy A | Optimization and Individualization of Medication Selection and Dosing |
US20070130109A1 (en) * | 2005-12-05 | 2007-06-07 | Raymond King | Metadata collection within a trusted relationship to increase search relevance |
US20070136371A1 (en) * | 2005-12-12 | 2007-06-14 | Mci, Inc. | Profile-based user access to a network management system |
US20070162443A1 (en) * | 2006-01-12 | 2007-07-12 | Shixia Liu | Visual method and apparatus for enhancing search result navigation |
US20070168546A1 (en) * | 2006-01-18 | 2007-07-19 | Microsoft Corporation | Efficient Dispatch of Messages Based on Message Headers |
US7779004B1 (en) * | 2006-02-22 | 2010-08-17 | Qurio Holdings, Inc. | Methods, systems, and products for characterizing target systems |
US20070225995A1 (en) * | 2006-03-17 | 2007-09-27 | Moore Barrett H | Method and Security Modules for an Incident Deployment and Response System for Facilitating Access to Private Civil Security Resources |
US20080040219A1 (en) * | 2006-08-09 | 2008-02-14 | Jeff Kim | Proximity-based wireless advertising system |
US20080046313A1 (en) * | 2006-08-17 | 2008-02-21 | Shuwei Chen | Methods and apparatus for serving relevant advertisements using web browser bars |
US7801901B2 (en) * | 2006-09-15 | 2010-09-21 | Microsoft Corporation | Tracking storylines around a query |
US20080104048A1 (en) * | 2006-09-15 | 2008-05-01 | Microsoft Corporation | Tracking Storylines Around a Query |
US20100328312A1 (en) * | 2006-10-20 | 2010-12-30 | Justin Donaldson | Personal music recommendation mapping |
US20080134086A1 (en) * | 2006-12-01 | 2008-06-05 | Institute For Information Industry | User interface apparatus, method, and computer readable medium thereof |
US20080140521A1 (en) * | 2006-12-12 | 2008-06-12 | Sivakumar Jambunathan | Dynamic Modification Of Advertisements Displayed In Response To A Search Engine Query |
US20080162537A1 (en) * | 2006-12-29 | 2008-07-03 | Ebay Inc. | Method and system for utilizing profiles |
US20080263022A1 (en) * | 2007-04-19 | 2008-10-23 | Blueshift Innovations, Inc. | System and method for searching and displaying text-based information contained within documents on a database |
US7644098B2 (en) * | 2007-04-24 | 2010-01-05 | Yahoo! Inc. | System and method for identifying advertisements responsive to historical user queries |
US20080300986A1 (en) * | 2007-06-01 | 2008-12-04 | Nhn Corporation | Method and system for contextual advertisement |
US20090070412A1 (en) * | 2007-06-12 | 2009-03-12 | D Angelo Adam | Providing Personalized Platform Application Content |
US20090063473A1 (en) * | 2007-08-31 | 2009-03-05 | Powerset, Inc. | Indexing role hierarchies for words in a search index |
US20090094093A1 (en) * | 2007-10-05 | 2009-04-09 | Yahoo! Inc. | System for selecting advertisements |
US20090106324A1 (en) * | 2007-10-19 | 2009-04-23 | Oracle International Corporation | Push-model based index deletion |
US20140189107A1 (en) * | 2007-11-27 | 2014-07-03 | Zettics, Inc. | System and method for sharing anonymous user profiles with a third party |
US20090216696A1 (en) * | 2008-02-25 | 2009-08-27 | Downs Oliver B | Determining relevant information for domains of interest |
US20090216750A1 (en) * | 2008-02-25 | 2009-08-27 | Michael Sandoval | Electronic profile development, storage, use, and systems therefor |
US20090216563A1 (en) * | 2008-02-25 | 2009-08-27 | Michael Sandoval | Electronic profile development, storage, use and systems for taking action based thereon |
US20090287683A1 (en) * | 2008-05-14 | 2009-11-19 | Bennett James D | Network server employing client favorites information and profiling |
US20090327327A1 (en) * | 2008-06-26 | 2009-12-31 | Sailesh Sathish | Method, apparatus and computer program product for providing context triggered distribution of context models |
US20100153324A1 (en) * | 2008-12-12 | 2010-06-17 | Downs Oliver B | Providing recommendations using information determined for domains of interest |
US20110276563A1 (en) * | 2010-05-06 | 2011-11-10 | Michael Sandoval | Systems, methods, and computer readable media for security in profile utilizing systems |
Cited By (114)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20120095827A1 (en) * | 1998-12-29 | 2012-04-19 | Vora Sanjay V | Structured web advertising |
US8707155B2 (en) * | 1998-12-29 | 2014-04-22 | Intel Corporation | Structured web advertising |
US9449001B2 (en) | 2005-10-26 | 2016-09-20 | Cortica, Ltd. | System and method for generation of signatures for multimedia data elements |
US10902049B2 (en) | 2005-10-26 | 2021-01-26 | Cortica Ltd | System and method for assigning multimedia content elements to users |
US9466068B2 (en) | 2005-10-26 | 2016-10-11 | Cortica, Ltd. | System and method for determining a pupillary response to a multimedia data element |
US9330189B2 (en) | 2005-10-26 | 2016-05-03 | Cortica, Ltd. | System and method for capturing a multimedia content item by a mobile device and matching sequentially relevant content to the multimedia content item |
US10742340B2 (en) | 2005-10-26 | 2020-08-11 | Cortica Ltd. | System and method for identifying the context of multimedia content elements displayed in a web-page and providing contextual filters respective thereto |
US9286623B2 (en) | 2005-10-26 | 2016-03-15 | Cortica, Ltd. | Method for determining an area within a multimedia content element over which an advertisement can be displayed |
US10848590B2 (en) | 2005-10-26 | 2020-11-24 | Cortica Ltd | System and method for determining a contextual insight and providing recommendations based thereon |
US9886437B2 (en) | 2005-10-26 | 2018-02-06 | Cortica, Ltd. | System and method for generation of signatures for multimedia data elements |
US9235557B2 (en) | 2005-10-26 | 2016-01-12 | Cortica, Ltd. | System and method thereof for dynamically associating a link to an information resource with a multimedia content displayed in a web-page |
US9792620B2 (en) | 2005-10-26 | 2017-10-17 | Cortica, Ltd. | System and method for brand monitoring and trend analysis based on deep-content-classification |
US9218606B2 (en) | 2005-10-26 | 2015-12-22 | Cortica, Ltd. | System and method for brand monitoring and trend analysis based on deep-content-classification |
US10949773B2 (en) | 2005-10-26 | 2021-03-16 | Cortica, Ltd. | System and methods thereof for recommending tags for multimedia content elements based on context |
US11620327B2 (en) | 2005-10-26 | 2023-04-04 | Cortica Ltd | System and method for determining a contextual insight and generating an interface with recommendations based thereon |
US10607355B2 (en) | 2005-10-26 | 2020-03-31 | Cortica, Ltd. | Method and system for determining the dimensions of an object shown in a multimedia content item |
US9747420B2 (en) | 2005-10-26 | 2017-08-29 | Cortica, Ltd. | System and method for diagnosing a patient based on an analysis of multimedia content |
US11604847B2 (en) | 2005-10-26 | 2023-03-14 | Cortica Ltd. | System and method for overlaying content on a multimedia content element based on user interest |
US9652785B2 (en) | 2005-10-26 | 2017-05-16 | Cortica, Ltd. | System and method for matching advertisements to multimedia content elements |
US11032017B2 (en) | 2005-10-26 | 2021-06-08 | Cortica, Ltd. | System and method for identifying the context of multimedia content elements |
US9646005B2 (en) | 2005-10-26 | 2017-05-09 | Cortica, Ltd. | System and method for creating a database of multimedia content elements assigned to users |
US9646006B2 (en) | 2005-10-26 | 2017-05-09 | Cortica, Ltd. | System and method for capturing a multimedia content item by a mobile device and matching sequentially relevant content to the multimedia content item |
US9639532B2 (en) | 2005-10-26 | 2017-05-02 | Cortica, Ltd. | Context-based analysis of multimedia content items using signatures of multimedia elements and matching concepts |
US9191626B2 (en) | 2005-10-26 | 2015-11-17 | Cortica, Ltd. | System and methods thereof for visual analysis of an image on a web-page and matching an advertisement thereto |
US11019161B2 (en) | 2005-10-26 | 2021-05-25 | Cortica, Ltd. | System and method for profiling users interest based on multimedia content analysis |
US10380623B2 (en) | 2005-10-26 | 2019-08-13 | Cortica, Ltd. | System and method for generating an advertisement effectiveness performance score |
US9558449B2 (en) | 2005-10-26 | 2017-01-31 | Cortica, Ltd. | System and method for identifying a target area in a multimedia content element |
US9396435B2 (en) | 2005-10-26 | 2016-07-19 | Cortica, Ltd. | System and method for identification of deviations from periodic behavior patterns in multimedia content |
US10387914B2 (en) | 2005-10-26 | 2019-08-20 | Cortica, Ltd. | Method for identification of multimedia content elements and adding advertising content respective thereof |
US11386139B2 (en) | 2005-10-26 | 2022-07-12 | Cortica Ltd. | System and method for generating analytics for entities depicted in multimedia content |
US11216498B2 (en) | 2005-10-26 | 2022-01-04 | Cortica, Ltd. | System and method for generating signatures to three-dimensional multimedia data elements |
US9489431B2 (en) | 2005-10-26 | 2016-11-08 | Cortica, Ltd. | System and method for distributed search-by-content |
US8880566B2 (en) | 2005-10-26 | 2014-11-04 | Cortica, Ltd. | Assembler and method thereof for generating a complex signature of an input multimedia data element |
US8880539B2 (en) | 2005-10-26 | 2014-11-04 | Cortica, Ltd. | System and method for generation of signatures for multimedia data elements |
US10733326B2 (en) | 2006-10-26 | 2020-08-04 | Cortica Ltd. | System and method for identification of inappropriate multimedia content |
US20090216563A1 (en) * | 2008-02-25 | 2009-08-27 | Michael Sandoval | Electronic profile development, storage, use and systems for taking action based thereon |
US20090216750A1 (en) * | 2008-02-25 | 2009-08-27 | Michael Sandoval | Electronic profile development, storage, use, and systems therefor |
US20100023952A1 (en) * | 2008-02-25 | 2010-01-28 | Michael Sandoval | Platform for data aggregation, communication, rule evaluation, and combinations thereof, using templated auto-generation |
US8402081B2 (en) | 2008-02-25 | 2013-03-19 | Atigeo, LLC | Platform for data aggregation, communication, rule evaluation, and combinations thereof, using templated auto-generation |
US8255396B2 (en) | 2008-02-25 | 2012-08-28 | Atigeo Llc | Electronic profile development, storage, use, and systems therefor |
US9244533B2 (en) * | 2009-12-17 | 2016-01-26 | Microsoft Technology Licensing, Llc | Camera navigation for presentations |
US20110154266A1 (en) * | 2009-12-17 | 2011-06-23 | Microsoft Corporation | Camera navigation for presentations |
US8984647B2 (en) | 2010-05-06 | 2015-03-17 | Atigeo Llc | Systems, methods, and computer readable media for security in profile utilizing systems |
WO2011151718A1 (en) * | 2010-06-04 | 2011-12-08 | Sean Grant Riley | Online advertising system and a method of operating the same |
GB2494597A (en) * | 2010-06-04 | 2013-03-13 | Ad Dynamo Internat Pty Ltd | Online advertising system and a method of operating the same |
US9053431B1 (en) | 2010-10-26 | 2015-06-09 | Michael Lamport Commons | Intelligent control with hierarchical stacked neural networks |
US9875440B1 (en) | 2010-10-26 | 2018-01-23 | Michael Lamport Commons | Intelligent control with hierarchical stacked neural networks |
US11868883B1 (en) | 2010-10-26 | 2024-01-09 | Michael Lamport Commons | Intelligent control with hierarchical stacked neural networks |
US11514305B1 (en) | 2010-10-26 | 2022-11-29 | Michael Lamport Commons | Intelligent control with hierarchical stacked neural networks |
US10510000B1 (en) | 2010-10-26 | 2019-12-17 | Michael Lamport Commons | Intelligent control with hierarchical stacked neural networks |
US20120173991A1 (en) * | 2010-12-31 | 2012-07-05 | Verizon Patent And Licensing, Inc. | Media Content User Interface Systems and Methods |
US8683349B2 (en) * | 2010-12-31 | 2014-03-25 | Verizon Patent And Licensing Inc. | Media content user interface systems and methods |
US20120173327A1 (en) * | 2011-01-03 | 2012-07-05 | International Business Machines Corporation | Promoting, delivering and selling information to intranet users |
US8661327B1 (en) * | 2011-01-06 | 2014-02-25 | Intuit Inc. | Method and system for automated insertion of relevant hyperlinks into social media-based communications |
US11620346B2 (en) * | 2011-03-14 | 2023-04-04 | Search And Share Technologies Llc | Systems and methods for enabling a user to operate on displayed web content via a web browser plug-in |
US11507630B2 (en) | 2011-03-14 | 2022-11-22 | Newsplug, Inc. | System and method for transmitting submissions associated with web content |
US20210397658A1 (en) * | 2011-03-14 | 2021-12-23 | Newsplug, Inc. | Systems and Methods for Enabling a User to Operate on Displayed Web Content via a Web Browser Plug-In |
US11947602B2 (en) | 2011-03-14 | 2024-04-02 | Search And Share Technologies Llc | System and method for transmitting submissions associated with web content |
US8732569B2 (en) | 2011-05-04 | 2014-05-20 | Google Inc. | Predicting user navigation events |
US10896285B2 (en) | 2011-05-04 | 2021-01-19 | Google Llc | Predicting user navigation events |
US9613009B2 (en) | 2011-05-04 | 2017-04-04 | Google Inc. | Predicting user navigation events |
US20120324043A1 (en) * | 2011-06-14 | 2012-12-20 | Google Inc. | Access to network content |
US20180246862A1 (en) * | 2011-06-14 | 2018-08-30 | Google Llc | Methods for prerendering and methods for managing and configuring prerendering operations |
US11019179B2 (en) | 2011-06-14 | 2021-05-25 | Google Llc | Access to network content |
US11032388B2 (en) * | 2011-06-14 | 2021-06-08 | Google Llc | Methods for prerendering and methods for managing and configuring prerendering operations |
US8788711B2 (en) * | 2011-06-14 | 2014-07-22 | Google Inc. | Redacting content and inserting hypertext transfer protocol (HTTP) error codes in place thereof |
US9928223B1 (en) * | 2011-06-14 | 2018-03-27 | Google Llc | Methods for prerendering and methods for managing and configuring prerendering operations |
US9769285B2 (en) | 2011-06-14 | 2017-09-19 | Google Inc. | Access to network content |
US8745212B2 (en) | 2011-07-01 | 2014-06-03 | Google Inc. | Access to network content |
US10332009B2 (en) | 2011-07-01 | 2019-06-25 | Google Llc | Predicting user navigation events |
US9530099B1 (en) | 2011-07-01 | 2016-12-27 | Google Inc. | Access to network content |
US9846842B2 (en) * | 2011-07-01 | 2017-12-19 | Google Llc | Predicting user navigation events |
US20130006897A1 (en) * | 2011-07-01 | 2013-01-03 | Google Inc. | Predicting user navigation events |
US8650139B2 (en) * | 2011-07-01 | 2014-02-11 | Google Inc. | Predicting user navigation events |
US8566696B1 (en) | 2011-07-14 | 2013-10-22 | Google Inc. | Predicting user navigation events |
US8744988B1 (en) | 2011-07-15 | 2014-06-03 | Google Inc. | Predicting user navigation events in an internet browser |
US10089579B1 (en) | 2011-07-15 | 2018-10-02 | Google Llc | Predicting user navigation events |
US9075778B1 (en) | 2011-07-15 | 2015-07-07 | Google Inc. | Predicting user navigation events within a browser |
US9146909B2 (en) * | 2011-07-27 | 2015-09-29 | Qualcomm Incorporated | Web browsing enhanced by cloud computing |
US20130031459A1 (en) * | 2011-07-27 | 2013-01-31 | Behrooz Khorashadi | Web browsing enhanced by cloud computing |
US20130046623A1 (en) * | 2011-08-17 | 2013-02-21 | Telefonaktiebolaget L M Ericsson (Publ) | Method For Providing a Recommendation, Recommender System, and Recommender Computer Program Product |
US20130066711A1 (en) * | 2011-09-09 | 2013-03-14 | c/o Facebook, Inc. | Understanding Effects of a Communication Propagated Through a Social Networking System |
US9430439B2 (en) | 2011-09-09 | 2016-08-30 | Facebook, Inc. | Visualizing reach of posted content in a social networking system |
US8655819B1 (en) | 2011-09-15 | 2014-02-18 | Google Inc. | Predicting user navigation events based on chronological history data |
US8600921B2 (en) | 2011-09-15 | 2013-12-03 | Google Inc. | Predicting user navigation events in a browser using directed graphs |
US9443197B1 (en) | 2011-09-15 | 2016-09-13 | Google Inc. | Predicting user navigation events |
US8862529B1 (en) | 2011-09-15 | 2014-10-14 | Google Inc. | Predicting user navigation events in a browser using directed graphs |
US9104664B1 (en) | 2011-10-07 | 2015-08-11 | Google Inc. | Access to search results |
US9584579B2 (en) | 2011-12-01 | 2017-02-28 | Google Inc. | Method and system for providing page visibility information |
WO2013078532A1 (en) * | 2011-12-02 | 2013-06-06 | Research In Motion Limited | Methods and devices for configuring a web browser based on an other party's profile |
US8793235B2 (en) | 2012-01-19 | 2014-07-29 | Google Inc. | System and method for improving access to search results |
US9672285B2 (en) | 2012-01-19 | 2017-06-06 | Google Inc. | System and method for improving access to search results |
US10572548B2 (en) | 2012-01-19 | 2020-02-25 | Google Llc | System and method for improving access to search results |
US20130254642A1 (en) * | 2012-03-20 | 2013-09-26 | Samsung Electronics Co., Ltd. | System and method for managing browsing histories of web browser |
US9946792B2 (en) | 2012-05-15 | 2018-04-17 | Google Llc | Access to network content |
US10754900B2 (en) | 2012-05-15 | 2020-08-25 | Google Llc | Access to network content |
US8843518B2 (en) * | 2012-07-17 | 2014-09-23 | Verizon Patent And Licensing Inc. | Method and apparatus for establishing a connection with known individuals |
US8887239B1 (en) | 2012-08-08 | 2014-11-11 | Google Inc. | Access to network content |
US20160048884A1 (en) * | 2012-09-27 | 2016-02-18 | Livingsocial, Inc. | Client-based deal filtering and display |
US10762535B2 (en) * | 2012-09-27 | 2020-09-01 | Livingsocial, Inc. | Client-based deal filtering and display |
US9141722B2 (en) | 2012-10-02 | 2015-09-22 | Google Inc. | Access to network content |
US9374411B1 (en) * | 2013-03-21 | 2016-06-21 | Amazon Technologies, Inc. | Content recommendations using deep data |
US10540720B2 (en) | 2013-09-30 | 2020-01-21 | The Toronto-Dominion Bank | Systems and methods for administering investment portfolios based on transaction data |
US20150095150A1 (en) * | 2013-09-30 | 2015-04-02 | The Toronto-Dominion Bank | Systems and methods for administering investment portfolios based on transaction data |
US20150095132A1 (en) * | 2013-09-30 | 2015-04-02 | The Toronto-Dominion Bank | Systems and methods for administering investment portfolios based on information consumption |
EP3007125A1 (en) * | 2014-10-08 | 2016-04-13 | Sears Brands, LLC | Member profiles and associated systems, methods, and media |
US20160378847A1 (en) * | 2015-06-26 | 2016-12-29 | Sri International | Distributional alignment of sets |
US10366108B2 (en) * | 2015-06-26 | 2019-07-30 | Sri International | Distributional alignment of sets |
US10817931B2 (en) * | 2015-08-26 | 2020-10-27 | Google Llc | Systems and methods for selecting third party content based on feedback |
US10223742B2 (en) * | 2015-08-26 | 2019-03-05 | Google Llc | Systems and methods for selecting third party content based on feedback |
US11232489B2 (en) | 2017-04-24 | 2022-01-25 | Consumer Direct, Inc. | Scenario gamification to provide actionable elements and temporally appropriate advertising |
US11514517B2 (en) | 2017-04-24 | 2022-11-29 | Consumer Direct, Inc. | Scenario gamification to provide improved mortgage and securitization |
US11386175B2 (en) * | 2017-09-28 | 2022-07-12 | Sharp Kabushiki Kaisha | Content recommendation apparatus, method of content recommendation, and content recommendation system |
US11853371B1 (en) * | 2018-07-31 | 2023-12-26 | Meta Platforms, Inc. | Logging information describing a type of event occurring in a mobile application received via an SDK incorporated into mobile application code of the mobile application |
Also Published As
Publication number | Publication date |
---|---|
JP5429498B2 (en) | 2014-02-26 |
EP2260408A2 (en) | 2010-12-15 |
EP2624152A1 (en) | 2013-08-07 |
CA2716432C (en) | 2014-05-06 |
EP2624153A1 (en) | 2013-08-07 |
CN102067119B (en) | 2016-04-27 |
WO2009108732A3 (en) | 2009-11-05 |
US8255396B2 (en) | 2012-08-28 |
US8402081B2 (en) | 2013-03-19 |
WO2009108732A2 (en) | 2009-09-03 |
WO2009108724A9 (en) | 2010-01-21 |
EP2260409A1 (en) | 2010-12-15 |
EP2626798A1 (en) | 2013-08-14 |
WO2009108724A2 (en) | 2009-09-03 |
JP2011513819A (en) | 2011-04-28 |
CA2805391C (en) | 2013-10-22 |
US20100023952A1 (en) | 2010-01-28 |
US20130151570A1 (en) | 2013-06-13 |
US20130138512A1 (en) | 2013-05-30 |
US20090216750A1 (en) | 2009-08-27 |
EP2354982A1 (en) | 2011-08-10 |
EP2624151A1 (en) | 2013-08-07 |
CN102067119A (en) | 2011-05-18 |
CA2716432A1 (en) | 2009-09-03 |
CA2805391A1 (en) | 2009-09-03 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US20090216639A1 (en) | Advertising selection and display based on electronic profile information | |
US11403351B2 (en) | Personalization techniques using image clouds | |
AU2017202248B2 (en) | Intent prediction based recommendation system | |
US20090216563A1 (en) | Electronic profile development, storage, use and systems for taking action based thereon | |
US9529910B2 (en) | Systems and methods for an expert-informed information acquisition engine utilizing an adaptive torrent-based heterogeneous network solution | |
US20200082437A1 (en) | Behavioral retargeting system and method for cookie-disabled devices | |
US9165060B2 (en) | Content creation and management system | |
US20150317398A1 (en) | Presenting non-suggested content items to a user of a social network account | |
US20130060858A1 (en) | Additional Systems and Methods for Curating Content | |
US9378529B2 (en) | Arranging stories on newsfeeds based on expected value scoring on a social networking system | |
US20200034917A1 (en) | Communication via simulated user | |
US20100185616A1 (en) | Systems and methods for predictive recommendations | |
US9336553B2 (en) | Diversity enforcement on a social networking system newsfeed | |
US20230224540A1 (en) | Systems and methods for generating a personality profile based on user data from different sources | |
US20150149433A1 (en) | System, device, and method for searching network data | |
KR20190108624A (en) | Systems and Methods for Improved Online Research | |
KR20140104626A (en) | System and method for contents recommendation, and apparatus applied to the same | |
CN117370660A (en) | Internet webpage display management method, equipment and computer storage medium | |
KR20150071081A (en) | Apparatus and method for managing advertisement s |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: ATIGEO LLC, WASHINGTON Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:KAPCZYNSKI, MARK JOSEPH;SANDOVAL, MICHAEL;DOWNS, OLIVER BRUCE;AND OTHERS;SIGNING DATES FROM 20090216 TO 20090305;REEL/FRAME:025369/0742 |
|
AS | Assignment |
Owner name: VENTURE LENDING & LEASING VI, INC., CALIFORNIA Free format text: SECURITY INTEREST;ASSIGNOR:ATIGEO LLC;REEL/FRAME:033654/0499 Effective date: 20140815 Owner name: VENTURE LENDING & LEASING VII, INC., CALIFORNIA Free format text: SECURITY INTEREST;ASSIGNOR:ATIGEO LLC;REEL/FRAME:033654/0499 Effective date: 20140815 |
|
AS | Assignment |
Owner name: ATIGEO CORPORATION, WASHINGTON Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:ATIGEO LLC;REEL/FRAME:035668/0825 Effective date: 20150515 |
|
AS | Assignment |
Owner name: VERITONE ALPHA, INC., CALIFORNIA Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:ATIGEO CORPORATION;REEL/FRAME:046302/0883 Effective date: 20171219 |
|
STCB | Information on status: application discontinuation |
Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION |