|Veröffentlichungsdatum||20. Aug. 2009|
|Eingetragen||13. Febr. 2009|
|Prioritätsdatum||13. Febr. 2008|
|Veröffentlichungsnummer||PCT/2009/34154, PCT/US/2009/034154, PCT/US/2009/34154, PCT/US/9/034154, PCT/US/9/34154, PCT/US2009/034154, PCT/US2009/34154, PCT/US2009034154, PCT/US200934154, PCT/US9/034154, PCT/US9/34154, PCT/US9034154, PCT/US934154, WO 2009/103028 A1, WO 2009103028 A1, WO 2009103028A1, WO-A1-2009103028, WO2009/103028A1, WO2009103028 A1, WO2009103028A1|
|Antragsteller||Three Purple Dots, Inc.|
|Zitat exportieren||BiBTeX, EndNote, RefMan|
|Patentzitate (2), Klassifizierungen (8), Juristische Ereignisse (4)|
|Externe Links: Patentscope, Espacenet|
SYSTEMS AND METHODS FOR CATEGORIZING DRAMATIC WORKS
 This application claims priority from earlier filed U.S. Provisional Patent Application Serial No. 61/028,486 filed February 13, 2008. The foregoing application is hereby incorporated by reference in its entirety as if fully set forth herein.
THIS DISCLOSURE IS PROTECTED UNDER UNITED STATES AND/OR INTERNATIONAL COPYRIGHT LAWS. © 2008-2009 THREE PURPLE DOTS. ALL RIGHTS RESERVED. A PORTION OF THIS DISCLOSURE OF THIS PATENT DOCUMENT CONTAINS MATERIAL WHICH IS SUBJECT TO COPYRIGHT PROTECTION. THE COPYRIGHT OWNER HAS NO OBJECTION TO THE FACSIMILE REPRODUCTION BY ANYONE OF THE PATENT DOCUMENT OF THE PATENT DISCLOSURE, AS IT APPEARS IN THE PATENT AND/OR TRADEMARK OFFICE PATENT FILE OR RECORDS, BUT OTHERWISE RESERVES ALL COPYRIGHT RIGHTS WHATSOEVER.
BACKGROUND OF THE INVENTION
 The decrease in the costs of movie production and distribution, the advance of "e-books," and the globalization of the film industry have all conspired to create a newly large range of titles for consumers. From this massive range of titles, there is simply not a way for consumers to discover dramatic works beyond the top titles heavily promoted by publishers and studios. Usually the titles most heavily promoted are placed at preeminent distribution points, such as national book stores and chain theaters. Book stores and chain theaters are generally not able to give equal treatment to the wide array of dramatic works. Currently, a consumer generally struggles to find a dramatic work they are most likely to enjoy if their friends haven't seen it, it hasn't been rated on any e-commerce site, and/or the work features no "famous or named actors" or "famous directors." Publishers of dramatic works have in common the need to sell as much product as possible, but they too are generally hampered by the relative inability to market dramatic works that do not feature known authors, actors or directors. These entities also have in common "back catalogues" of product that they have been unable to successfully market.
 For example, e-Commerce sites like Amazon.com and Netflix are searchable by consumers only by the name of the dramatic work, genre, actor or director. All of these methods require the consumer to know the name of one of the elements for which they would search. E-Commerce sites also utilize different flavors of "collaborative filtering" which all, in one way or another, suggest that consumer A will like a given work because that work has been purchased by consumers B, C and D who have purchased titles similar to those consumer A has chosen. This model is still flawed in that neither consumers A, B, C or D have the ability to find dramatic works to purchase on these sites without knowing a name of one of the elements above described. These e- commerce sites must also intelligently stack-rank the search results displayed to the consumer with regard for the phrase the consumer selected. The combination of element- based search and the collaborative filter is helpful but is limited by the necessity of a consumer searching for a known element. When using an e-commerce search site, results to a search are "stack ranked." Commonly the results are drawn from what is most commonly mentioned or linked to an online methodology. The methodology is mathematically pre-disposed to return dramatic works that are the most widely known. To compound that problem, the graphical representation of search results must also be "stack ranked" to fit the computer screen which once again forces a default display which features the most common titles.
BRIEF DESCRIPTION OF THE DRAWINGS
 The preferred and alternative embodiments of the present invention are described in detail below with reference to the following drawing:
 FIGURE 1 shows a screenshot of a StoryLab™ in one embodiment;
 FIGURE 2 schematically illustrates one method of establishing a DSS Database;  FIGURE 3 is a schematic illustration the Story Arc™ portal;
 FIGURE 4 is a schematic illustration of communication of the StoryArc™ Dramatic Story Score (DSS) algorithm a search engine, as well as technological receptor which can have a decoder for the algorithm; and
 FIGURES 5-10 depict a StoryArc™ website destination. DESCRIPTION OF THE MULTIPLE EMBODIMENTS
 In one embodiment of the invention, StoryArc™ is comprised of technology utilizing a combination of heuristics and crowd- sour cing techniques: a database, a tool bar, a search engine and a text and audio screener. It preferably includes the ability to use technology to find, measure, rate, and share attributes about a dramatic work which make the dramatic work more assessable to consumer users.
 In one embodiment, systems and methods for determining the "dramatic story score" of any dramatic work is disclosed herein. The systems and methods preferably categorize the dramatic qualities of any filmed or written dramatic work without regard to writer, actor, genre, language, consumer appeal, consumer rating or collaborative filtering. In one embodiment, used primarily by consumers, the system and method provides consumers an omnibus search and recommendation tool for dramatic works. The recommendation is based on what the consumer will enjoy based solely upon the dramatic qualities of the works for which the consumer expresses appreciation.
 For publishers of dramatic works, the system and method offers a way to advertise works to consumers. The advertised works presented to the consumer are those that they are most likely to appreciate, based solely upon the individual consumer's favorite dramatic works, without regard to writer, actor, genre, language, consumer appeal, consumer rating or collaborative filtering.
 The systems and methods described herein provide advertisers and advertising insertion companies a new form of targeting advertising. The advertising can be strategically placed into the display of dramatic work which allows the advertiser the ability to target specific characters, storylines, or dramatic moments within the work. For instance, an advertiser could target ads adjacent to "the comic relief moment" with a comic ad or they could target dramatic ads to the "calm before the storm" dramatic moment. The system and method provides general advertisers and public relations professionals with a method for crafting messages to consumers that are created to favorably compare to their favored story structure and for targeting these same messages to the proper consumer. The systems and methods provide e-commerce sites with a searchable omnibus of movies that a particular consumer is likely to enjoy. The e- commerce site can proactively offer consumers movies based upon what the consumer has purchased in the past.
 For filmmakers without deep promotion budgets, the systems and methods provide a way to attached meta data to their works, like a digital file of a movie or book or to their website. Consumers can use the meta date to find works that would otherwise go un-discovered. The system and method further provides search engines with a new class of meta data in order to provide better returns for inquiries about dramatic works.
 If a consumer particularly loves a specific type of story, they will generally use a search product that looks for none of the above, but, instead, provides search returns based upon the very nature of the stories they already enjoy.
 In one embodiment, the system and method preferably queries the consumer about the dramatic works they already enjoy and are a preference. This exemplary method requires little input from another consumer. The system and method can return search results based upon the degree to which a set of dramatic works in an omnibus database of stories match indicated by the consumer as a preference.
 The system and method preferably provides a scene-by-scene ranking/score of a dramatic work based on the dramatic qualities of the overall story, the particular scene, the characters in the overall story, the character in a particular scene, location the scene was filmed, and weather conditions of each scene. By way of example, in filmed dramatic works, the camera angles, lighting types, presence of ambient sounds, background or featured music are ranked. Each ranking of these elements of a story is placed into a time-stamped "story-map" of each dramatic work, culminating in a dramatic- story- score (DSS) for each element tracked. The amalgamation of the DSS for each element in each story builds a resulting story algorithm for each dramatic work.
 In one embodiment, the system and method optionally creates a communicable algorithm that describes the nature and details of each story to TheStoryArc.com search engine, as well as any technological receptor which has licensed the decoder for the algorithm. Some potential licensed decoders include a search-engine, a web-portal, an advertising insertion engine, and/or an e-commerce site. Licensees of the DSS can then allow their users to search for dramatic works using the method described herein.
 The algorithm can also be embedded into the actual digital assets of the story, such as an e-Book, or encoded video file. When a consumer uses a digital asset containing the algorithm on a device connected to the Internet or in some other manner accessible to servers, the system and method observes consumer interaction with the digital media asset to preferably determine the points in the consumption of a story that a consumer pauses, ends consumption or rewinds to watch or read a scene again. Each of these actions results in a ranking by the system.
 In one embodiment, a consumer search site is created where registered consumers can search for stories based upon their favorite stories and their favorite elements within those stories.
 In one embodiment, the system and method creates a collection of consumers with defined tastes for defined story-types.
 In another embodiment, using the category/ story-type of "drama" as an example: a method for profitably distributing "dramatic" works and to successfully marketing what may be niche works of "drama" is created. The system and method enables publishers to distribute both a more diverse catalogue and to market the back catalogue in a way more preferable to dramatic works that do not feature known names. These entities can use the combined services and technologies to target advertising for dramatic works to consumers most likely to find appeal in the actual story type without regard to the principle creators of the dramatic work.
 Included herein is a searchable omnibus of dramatic works categorized not by genre, writer, actor, director or by "collaborative filtering"but by the very make-up or "DNA" of the actual story. Some variations analyzed are included in the following non exclusive list: story arc, scene arc, character arc, story type, scene type, character type, source of conflict, level of conflict, intensity of conflict, setting, location and/or weather. Each of the variations receives a ranking score, preferably the range score is between 1 and 10 which in one embodiment creates millions of variations for DSS scores. The heuristically populated database records all of the attributes of a story. For example, in written works, the attributes are codified by page. In filmed works, the attributes are time stamped or are codified in more organic increments related to the story. Each story is given a dramatic story score (DSS), which is an algorithm constructed by the amalgamation of the database scores for each story factor combined to form a searchable relatable line of code. The DSS score, as applied to a group of stories, relates dramatic works not by the elementary methods of writer, actor, genre, director or the assumptive collaborative filter, but by actual DNA of each story. The DSS and the Story Arc algorithm can be decoded by any technological receptor that has licensed the de-coder. Licensees can include, but are not limited to, a search-engine, a web-portal or and advertising insertion engine.
 A StoryLab™ is a live-time application that surrounds the story source, written or filmed, with the device that trained "story- watchers" use to attribute the DSS- factors to a plurality of story elements.
DESCRIPTION OF A PREFERRED EMBODIMENT
 The StoryArc™ Dramatic Story Score (DSS) Database can be first populated by rating the dramatic qualities of any filmed or written dramatic work for example, — based on a plurality of operatives or attributes in a given dramatic work, including but not limited to the following: story arc, scene arc, character arc, story type, scene type, character type, source of conflict, level of conflict, intensity of conflict, setting, location, weather, and the like. A database can be heuristically populated wherein a plurality of attributes of a dramatic work are given a ranking, the range of each attribute can be for example, a ranking from 1-10. In addition, within a written dramatic work the attributes can be ranked per page, and in filmed works the attributes can be time-stamped in organic increments for example, relating to scene, dramatic climax , and the like. The aggregation of ranked attributes for an individual dramatic work is that particular work' "Dramatic Story Score (DSS)", an algorithm constructed by the amalgamation of the database scores for each story attribute combined to form a searchable relatable line of code. Based on the ranked attributes and thereby a DSS, an omnibus search and recommendation tool can return results to the consumer based on a consumer query, and further refined by consumer-identified attributes for the works for which the consumer expresses an appreciation.
 In FIGURE 1, one embodiment of the invention is schematically illustrated. A StoryLab™ application can overlay the dramatic work source. A trained story watcher can use the StoryLab™ application while reviewing the dramatic work source. The trained story watcher can assign a DSS to reviewed dramatic works by ranking a plurality of attributes of the dramatic work. A Story Arc™ Master Database can house the Dramatic Story Score (DSS) data of reviewed dramatic works.
 In FIGURE 2 one method of establishing a DSS Database is schematically illustrated. In this exemplary embodiment, as a first step in establishing a DSS Database, a baseline DSS score for the top 1000 most popular movies can be used as the dramatic work input source. Trained story watchers can use the StoryLab™ application to assign a DSS once having reviewed dramatic works and ranking a plurality of attributes. As a next step, the DSS data and Story Arc™ and/or StoryLab™ applications can be licensed to publishers of other larger bodies of dramatic works, thus increasing the dramatic works entered into the DSS database. As schematically illustrated in FIGURE 3, the StoryArc™ portal can grow virally by using this collaborative cross-fertilization scenario. Collaborating publishers can both contribute to the DSS rankings and also share the data stored in the Master Database. Each participant in the process is enabled with ranking tools. A publisher that uses the system can attach a DSS score to a digital asset or the server/web page that hosts the asset making dramatic works crawlable. The StoryArc™ portal optimally retains amalgamated dramatic works data and consumer information in the Master DSS Database.
 As schematically illustrated in FIGURE 4, the StoryArc™ dramatic story score algorithm can be communicated to a StoryArc™ search engine, as well as technological receptor which can have a decoder for the algorithm. In a preferred embodiment, potential licensed decoders include search engines, web-portals, advertising insertion engines, and/or e-commerce sites.
 In another embodiment, StoryArc™ can be a search portal. The DSS search engine allows consumers as well as publishers to search for dramatic works, wherein the returned results of their dramatic works query is based on the DSS and the consumer defined preferences.
 StoryArc™ can be both a utility and second a destination. The utility can be an Alert-bar that can track, search, and recommend dramatic works that a consumer might find of interest based on the consumers profile stored in the Master DSS Data Base. It is also the home of StoryArc search tool.
 FIGURES 5-10 depicts a StoryArc™ website destination providing users and consumers with searching tools, including but not limited to, tertiary key word searching, but also provides for secondary ads to partner sites facilitating behavioral targeting. In this exemplary scenario, a consumer is prompted with questions, including preference questions about the consumers dramatic work preferences, for example "Tell us your five favorite movies,"(FIGURE 7) as well as what sources they would like to use for the search (FIGURE 6). The consumer can be prompted with additional questions based on more specific metrics, e.g., based on pages in a written work, or scenes in a film (FIGURE 9). Based on the DSS scores attributable to the consumer query, and the initial consumer input from the prompted questions the Story Arc™ search portal automatically scans the Web for stories with DSS closest to the ones the consumer likes. In another embodiment and as schematically illustrated in FIGURE 10 a StoryFind™ application can constantly search for stories that are most like the ones the consumers are likely to appreciate, and provide updates to the consumer by alerts which can be, for example, delivered to a consumer by email or text alerts.
 While the preferred embodiment of the invention has been illustrated and described, as noted above, many changes can be made without departing from the spirit and scope of the invention. Accordingly, the scope of the invention is not limited by the disclosure of the preferred embodiment.
|US5659732 *||17. Mai 1995||19. Aug. 1997||Infoseek Corporation||Document retrieval over networks wherein ranking and relevance scores are computed at the client for multiple database documents|
|US20060212367 *||7. Juni 2006||21. Sept. 2006||Gross John N||Method of selecting and distributing items to consumers of electronic media|
|Unternehmensklassifikation||G06Q10/10, G06F17/3082, G06F17/30705, G06F17/30828|
|Europäische Klassifikation||G06Q10/10, G06F17/30E, G06F17/30T4|
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