WO1997046958A1 - A relational database system containing a multidimensional hierarchical model of interrelated subject categories with recognition capabilities - Google Patents
A relational database system containing a multidimensional hierarchical model of interrelated subject categories with recognition capabilities Download PDFInfo
- Publication number
- WO1997046958A1 WO1997046958A1 PCT/US1997/009729 US9709729W WO9746958A1 WO 1997046958 A1 WO1997046958 A1 WO 1997046958A1 US 9709729 W US9709729 W US 9709729W WO 9746958 A1 WO9746958 A1 WO 9746958A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- technical
- patents
- database
- scientific
- documents
- Prior art date
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S707/00—Data processing: database and file management or data structures
- Y10S707/912—Applications of a database
- Y10S707/923—Intellectual property
- Y10S707/924—Patent procedure
- Y10S707/929—Docketing
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S707/00—Data processing: database and file management or data structures
- Y10S707/953—Organization of data
- Y10S707/954—Relational
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S707/00—Data processing: database and file management or data structures
- Y10S707/953—Organization of data
- Y10S707/956—Hierarchical
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S707/00—Data processing: database and file management or data structures
- Y10S707/953—Organization of data
- Y10S707/957—Multidimensional
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10S—TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10S707/00—Data processing: database and file management or data structures
- Y10S707/99941—Database schema or data structure
- Y10S707/99944—Object-oriented database structure
- Y10S707/99945—Object-oriented database structure processing
Definitions
- the present invention is a database.
- the present invention is multi-dimensional database that models a business or scientific or technical body of work. Relational databases are well known and have been used to manipulate discrete numerical values. There are many commercial databases available which permit the user to build relationships between tables and some of these databases allow large text fields to be stored and manipulated.
- Mathematical methods similar to weighted sum have been used against numerical measurements based on physical phenomena to measure contributions to gross mechanical properties.
- An example is a weight average of polymer concentrations of a particular molecular weight and their contributions to the overall gross physical properties of the polymer.
- the present invention is a database system and a method of producing that database which can be used to assign scientific or technical documents, such as patents and/or technical or scientific publications and/or abstracts of these patents or publications, to one or more scientific or technical categories within a multidimensional hierarchical model which reflects the business, scientific or technical interests of a business, scientific or technical entity or specialty.
- Lower level categories which reflect scientific concepts and technology may be recognized and assigned by use of a set of expert technical searches (ETS).
- ETS expert technical searches
- Higher level, more abstract, concepts may be recognized and assigned by mathematically manipulating the matrix of lower level scientific and technology concepts, in combination with a matrix of contributions to higher level concepts, which reflects the stored cumulative expertise of a team of technical or scientific experts.
- the population of each category, within the multidimensional hierarchy may be used to prepare graphical and/or tabular overviews which reflect the research activity within a business or technical entity or specialty over a span of years and across an unlimited number of dimensions.
- the graphical and/or tabular overviews allow trends and discontinuities to be readily identified.
- the apparent trends and discontinuities may be verified by examining the individual documents and/or abstracts and/or patent claims, and/or all associated fields which contribute to both the overall trends and any specific trends within a business entity or technical specialty.
- Specific detail on individual documents and/or abstracts and/or claims may also be captured in discrete fields and linked to the categories within the hierarchical model and the technical documents and/or abstracts and/or claims. All of the above data may also be linked to full-text sources of the documents.
- Figure 1 shows a schematic diagram of the database.
- Figure 2 shows one type of graphical display using the database of the present invention.
- Figure 3 shows the graphical display for Example 3.
- Figure 4 shows the graphical display of Table 6.
- the present invention is a database system which contains a hierarchical model of a complex business, scientific or technical entity or specialty and the associated technical documents, such as patents or scientific or technical publications, or abstracts of those patents or publications, which reflect each aspect of that model.
- Each technical document may be assigned to one or more categories within the hierarchical model.
- the model and associated technical documents and/or abstracts and/or technical indexing may be used to dete ⁇ nine trends and discontinuities within the bounds of the model and may also be used to project unanticipated trends and discontinuities beyond the bounds of the model.
- the individual documents and/or abstracts within one or more categories or subsets of categories may be displayed along with the corresponding US claims and/or European granted or application claims by use of a relational database which is viewed through a computerized graphical interface.
- This database disaggregates a set of patents and/or technical documents into discrete technical categories by use of a set of pre-defined search protocols which match the scientific or technical concepts within the model.
- the pre-defined search strategies automatically categorize the set of technical documents to fit the multidimensional hierarchical model of a scientific or business discipline.
- the pre-defined search strategies may be conducted on a commercial database system and the results of these searches stored in a local electronic database. Alternatively, the pre-defined search strategies may be conducted in a local electronic database containing records captured from a commercial database system or by a combination of these two methods.
- the categorization may then be used by the relational database to identify trends and discontinuities in the research efforts represented by the technology in the underlying technical documents and/or patents.
- the categorization may also be used to allow the technical experts to drill-down and examine the underlying documents and/or abstracts and/or claims which contribute to these trends and discontinuities.
- the overall goal of this method is to use this model to identify unanticipated trends and discontinuities in the pattern of research effort in a technical, scientific or business entity or discipline as reflected by the technical documents and/or patents obtained by that scientific or business entity or discipline, where the overall pattern itself has been previously hidden due to both the complexity of the individual documents and the large number of documents being considered.
- this method of analysis may be used to confirm anticipated trends and discontinuities in the pattern of research effort in a technical, scientific or business entity or discipline as reflected by the technical documents and/or patents obtained by that scientific or business entity or discipline, where the overall pattern itself has been previously hidden due to both the complexity of the individual documents and the large number of documents being considered.
- the documents and/or abstracts and/or claims and/or technical indexing may be electronically stored in a relational database and linked to the categorization which reflects the overall hierarchical model.
- the documents and/or abstracts and/or claims and/or technical indexing may be displayed on a computerized graphical interface. All of the documents may be displayed or only those documents within one or more categories may be displayed or only those documents within a subset of one or more categories may be displayed. Subsets of all of the documents and/or subsets of one or more of the categories may be selected by further searching of any of the stored data. These subsets of documents and/or abstracts and/or claims may be displayed on a computerized graphical interface.
- the relational database can also contain subject-specific tables of technical details such as catalyst precursors, cocatalysts, reaction conditions, reactor types, or product characteristics, which are captured in a discrete form by scientists evaluating the underlying patents or technical documents.
- the relational database can also contain links to full-text sources of patents or technical documents either in a database, on a CD-ROM, a local LAN, a Wide-Area-LAN or on the Internet.
- the retrieved full-text patents may include the full text of US and/or foreign patents or published patent applications and may also include images of the full patents or a combination of text and images.
- the retrieved full text technical documents may also include the full text and or images of scientific or technical publications.
- the present database can be used to answer a number of questions.
- the database can be used to identify the overall pattern of research activity, as reflected in the number of patents or technical documents.
- the database can also be used to identify trends and discontinuities across the multidimensional hierarchy which is needed to model complex scientific, technical and business disciplines. Specifically this database can pose questions such as:
- the computer system In order to create a computer system which can answer higher level questions such as these, the computer system must have a pre-defined model of the overall scientific or business discipline and the computer system must have already analyzed the technical content of each patent or technical document with respect to that model.
- the system of sophisticated technical searches and the method of applying those searches to a set of technical documents, such as patents, to categorize those documents to match a multidimensional hierarchy which models a scientific or business entity or discipline is the subject of this patent memo.
- the relational database can also contain subject-specific tables of technical details such as catalyst precursors, cocatalysts, reaction conditions, reactor types, product characteristics, which are captured in a discrete form by scientists evaluating the underlying patents.
- the original classification serves to group similar patents together.
- An individual scientist or engineer may then evaluate each patent in a particular group and capture the essential details of each invention into a subject-specific table which can be linked back to the original documents and/or abstracts and to the original categorization.
- the expert analysis can also feed back into the categorization of the patents to enhance the categorization achievable by sophisticated technical searches.
- Figure 1 shows a high-level overview of the database design covered by this invention, with increasing levels of abstraction. Stage I is the least abstract and Stage VI is the most abstract.
- Stages I and II represent well known methods of dealing with collections of full-text patents and semi-organized analyses of those collections of patents in the form of spreadsheets or small databases.
- Stage III through VI represent the subject of this invention whereby increasingly abstract concepts and overviews can be derived from a collection of electronically available patent abstracts, and/or technical documents, technical indexing, and patent claims.
- Stage I represents the actual patents or technical documents, whether in a stack of paper copies or in an electronic collection on a CD-ROM, in a database, on a LAN or on the Internet.
- Stage II represents commonly used methods of analyzing full-text patents and/or technical documents and storing that patent-by-patent analysis in the form of subject-specific spreadsheets, and small databases.
- An enhancement represented by the current invention is that these detailed analyses can then be electronically linked to a given patent and/or patent family and electronically displayed along with the Patent Abstracts and/or Patent Claims and/or technical documents.
- Stages III through VI represent the database design of this invention.
- Stage III represents the electronic capture of Patent Abstracts, and/or technical documents and the parsing of the complex, multi-entity data fields which usually accompany these Patent Abstracts, such as the Patent Inventors, Patent Numbers, Patent Companies (Assignees), Patent Legal Status and Patent Priority data.
- the Parsed Patent Number Record would capture a separate record for each patent equivalent including the patent number, publication date and patent status. Similar levels of detail are captured for each parsed field.
- Also represented at this level is the electronic capture of the US Claims and the European Claims (granted patent and published applications) and associated information such as inventor and assignee. All of these fields are electronically linked and may be electronically displayed as a set of information pertinent to one particular patent and/or patent family on a computerized graphical interface.
- Technical Documents may be similarly captured and the associated complex fields parsed to yield normalized data.
- Stage IV represents the design of a Customized Technical Subject Hierarchy which models the specific interests of a business entity or technical or scientific specialty and the many facets of that entity or specialty.
- the hierarchical model consists of two or more levels, each level consisting of sets of categories which define the concepts being modeled. For example, this method models business, scientific, or technical entities and/or specialties at two levels in the same sense as a Genus-Species relationship. The higher level terms would correspond to a broader, more abstract genus and the lower level categories would correspond to a more specific set of sub-categories corresponding to the species.
- a multiplicity of levels can be employed to capture complex topics which require more than two levels of abstraction.
- This Technical Subject Hierarchy is used to create a set of sophisticated expert technical searches (ETS), using the best chemical and technical indexing available along with the text of the patent abstracts and/or the patent claims and/or the technical document.
- ETS expert technical searches
- An expert search is created to identify patents or technical documents that are pertinent to each individual category within the Customized Technical Subject Hierarchy and the results of these searches are electronically stored in tables represented by Stage V. The stored results are electronically linked to the corresponding patent and/or patent family.
- Stage IV Automatically feeds into Stage V.
- the set of expert searches represented by Stage IV can be automatically executed against a new set of patents and/or technical documents.
- This new set of patents and/or technical documents may represent either recently published patents or technical documents and/or recently identified patents or technical documents and/or older collections of patents or technical documents which are now being captured with the methods of this invention.
- Stage V represents the stored assignment of each patent to one or more of the categories in the Customized Technical Subject Hierarchy of Stage IV.
- each category is populated with records that match the search criteria.
- the automatic execution of expert technical searches analyze the indexing, abstract, text and/or claims for each patent and assign each patent and/or technical document to one or more categories in the Customized Technical Subject Hierarchy of Stage IV.
- Stage V includes one or more Fractional Contribution Matrices which may be used to derive more abstract concepts from the existing categorization.
- the Fractional Contribution Matrices are created by collecting the combined expertise of acknowledged experts in a technical or scientific field and representing this expertise in a stored matrix. This Fractional Contribution Matrix represents the cumulative expertise of a set of technical experts as to how much a lower level scientific or technology category will contribute to a higher-level, more abstract concept.
- the database system allows patents and/or technical documents to be electronically captured and analyzed at a convenient time. This set of analyzed patents and/or technical documents may then be used to identify trends and discontinuities in the overall pattern of research efforts represented by the set of patents or technical documents. These trends and discontinuities may be identified any time following the analysis of the set of patents and/or technical documents.
- the stored analysis may be used minutes, days, months or years later.
- Stage VI represents a high-level overview of a business, scientific or technical entity or specialty and provides a method for grasping the pattern of research effort represented by a collection of patents or technical documents. These patterns are obscure at Levels I and II, and can only be clearly observed after pursuing the methods of this invention to achieve the higher level abstraction represented by Stages III through VI.
- the dashed line from Stage V to Stage I represents the fact that the data stored in the database, and all associated analyses of Stages II through VI, may be used to identify patents and/or technical documents of particular interest for a particular application.
- the patent numbers for this set of patents may then be used as unique identifiers to electronically link to full text sources of patents and display the full text and associated graphic images of the set of patents.
- the electronic full text sources of these patents may be on a CD-ROM, in a database, a LAN or on the Internet. Unique Identifiers may similarly be used to link to sources of full-text technical or scientific documents.
- the unstructured text in technical documents is reduced to fit a multidimensional hierarchy which models a complex system of scientific or business information, such as that represented by the body of patents pertinent to a particular scientific or business discipline.
- This method utilizes sophisticated expert technical searches (ETS) to automatically categorize technical documents, such as patents or scientific publications.
- ETS expert technical searches
- This method disaggregates a set of patents or technical documents into discrete technical categories by use of a set of pre-defined search protocols to assign each document to one or more categories.
- a complex set of technical and/or scientific search strategies may be produced to identify and automatically categorize documents to fit a pre-defined matrix of technical categories.
- the matrix of technical categories models a scientific, engineering or business area and may consist of hundreds of categories on one or more levels of abstraction.
- Each category has a unique set of characteristic terms associated with it.
- a predefined set of search parameters would be created comprised of technical search terms such as
- the expert technical and/or scientific searches use all the expertise of a skilled technical searcher and capture that expertise in a set of pre ⁇ defined search strategies.
- These pre-defined search strategies may be run against one or more sets of technical documents, such as patents assigned to a particular business or scientific entity or in a particular technical specialty.
- the pre ⁇ defined search strategies automatically categorize the set of technical documents to fit the multidimensional hierarchical model of a scientific or business discipline.
- the pre-defined search strategies may be conducted on a commercial database system and the results stored in a local electronic database or the pre ⁇ defined search strategies may be stored and executed in a local electronic database containing records captured from a commercial database system.
- the categorization may then be used to identify trends and discontinuities in the research efforts represented by the technology in the underlying technical documents and/or patents.
- mathematical relationships may be applied against the matrix of technical categories to extract hidden details and patterns and to generate additional levels of abstraction.
- Example 1 shows the logic for automatically assigning patents to a pre-defined subject-specific-hierarchy, using a series of expert technical searches (ETS). Similar methods could also be used to automatically categorize scientific and/or technical publications.
- ETS expert technical searches
- Example I Automatically Assigning Patents to Categories Within a Hierarchical Model of a Business or Technical Specialty
- ETS expert technical search
- Example 2 shows a portion of a Subject Hierarchy which could be used to model a business or technical entity.
- an expert technical search ETS
- ETS expert technical search
- Example 2 makes no attempt to categorize all Biopolymers, but rather only categorizes those Biopolymers of interest to a particular business or technical specialty.
- Example 2 A Partial Hierarchy representing the Interests of a Particular Business or Technical Specialty
- Example 3 shows two sample expert technical searches (ETS) which could be created to identify those patents or technical documents which should be assigned to subjects within the Partial Subject Hierarchy of Example 2.
- ETS electronic expert technical searches
- Example 3 shows the expert technical searches needed to identify patents which should be assigned to category 1010 (Phosphorus-Modified Biopolymers) and to category 1020 (Polyester-type Biopolymers) within the Subject Hierarchy of Example 2.
- Example 3 The expert subject searches in Example 3 would be further modified and customized to fit the particular needs of a specific hierarchical model.
- the overall database might be focused on oil well drilling additives or it might be focused on cosmetic formulations.
- the searches would be further refined to selectively retrieve one set of patents or technical documents for a database focused on fluid loss control additives, for use in oil well drilling fluid additives, and to selectively retrieve a different set of patents or technical documents for a database focused on cosmetic formulations.
- each patent has been automatically assigned to one or more categories within the Subject-Specific-Hierarchy and linked to the parent patent record in the relational database.
- the complex, multi-entity data fields have been parsed to multi-field tables and linked to the parent patent or technical document record in the relational database.
- Table 3 and Figure 2 show two of the simplest displays possible using these Subject-Categories.
- Table 2 shows a portion of the table which stores the assigned Subject-Categories. These are the same Subject-Category assignments that are created by using stored expert technical searches (ETS) to assign individual patents or technical documents to the categories within a Subject-Specific- Hierarchy. These stored categoiy assignments may be used to create a tabular display of the subject-assignments over a span of years as shown in Table 3. These categories may also be used to create a graphical display of the subject- assignments over a span of years, as shown in Figure 2.
- Table 2 shows a portion of the table which stores the assigned Subject-Categories. These are the same Subject-Category assignments that are created by using stored expert technical searches (ETS) to assign individual patents or technical documents to the categories within a Subject-Specific- Hierarchy. These stored categoiy assignments may be used to create a tabular display of the subject-assignments over a span of years as shown in Table 3. These categories may also be used to create a graphical display of the subject- assignments over
- Example 3 shows the logic of creating a display by company, of the top 15 inventors, by inventor (one inventor per page), by subject-category (one subject-category per line), per year (one count of patents per column) with totals accumulating the total number of patents filed by a particular inventor in a particular company across a span of years.
- the inventors may be sorted by the total number of patents filed within a selected set of subject-categories, within a selected range of years, within a particular company and displayed in a series of tabular and graphical displays.
- the first page would display a tabular or graphical overview of the number of patents filed by the most active inventor, in each category, within company XYZ, over a span of years.
- the next page would display a tabular or graphical overview of the number of patents filed by the next most active inventor, in each categoiy, within company XYZ, over a span of years and so on for the top 15 inventors.
- a display of this type could be used to identify trends and discontinuities in the research activity of the most prolific inventors within a company. Similar methods could be used to display the activities of authors of technical and/or scientific documents.
- This invention further includes the method of deriving more abstract concepts from the set of stored category assignments, by applying mathematical methods to extract these more abstract concepts.
- These more abstract concepts can not be readily identified by the application of expert technical searches alone. However, a method of quantifying the research effort expended in the areas defined by each of these more abstract concepts is of great value.
- These more abstract concepts can be identified by the use of both the matrix of technical and/or scientific concepts, identified by the application of expert technical searches, and a matrix of stored expert opinion.
- the matrix of stored expert opinion represents the cumulative opinion of a group of expert technical staff and/or scientists, on the fractional contribution of each technical and/or scientific concept to each of the higher-level, more abstract concepts.
- the present database includes a multidimensional hierarchy of subject categories wherein the different levels of the hierarchy are interrelated by a mathematical formula.
- the mathematical formula which interrelates the different levels takes the form of a sum of an aggregate count of unique items in a category multiplied by weighting factors for each category in the next higher (more abstract) level.
- Each higher (more abstract) level of the hierarchy is therefore a weighted sum of contributions from each category in the previous level.
- the aggregate count of unique items is arrived by modeling a scientific or business discipline based on the technical content of patents and/or technical documents in that scientific or business discipline.
- the weighting factors are derived by the cumulative knowledge of experts in that scientific or business discipline to reflect the impact of each technical category on the next the higher level of the hierarchy.
- f(xl) sum((attribute- 1 * weighting-factor- 1 )+(attribute-2* weighting-factor- 1)+%)
- f(x2) sum((attribute- 1 *weighting-factor-2)+(attribute-2* weighting-factor-2)+
- f(x3) sum((att ⁇ ibute-l *weighting-factor-3)+(attribute-2*weighting-factor-3 )+10)
- weighted averages may also be calculated across a span of years to reflect a multidimensional representation of research efforts across a span of technologies and across a span of years.
- the Higher Level Subject Categories may be derived by matrix manipulation of two matrices, one representing the known subject category assignments in a hierarchical model of a business or technical specialty, and the other matrix, representing the cumulative knowledge of technical experts in a given business or technical entity or specialty.
- Table 4 shows a two dimensional matrix which represents the number of patents assigned to selected subject categories across a selected span of years. Table 4 may represent the patents filed by an entire company, or the patents filed in a particular business enterprise, or the patents filed by a particular inventor within a particular company or business enterprise, as examples.
- Table 5 represents the cumulative knowledge of a group of technical experts in a given business or technical entity.
- Table 5 may represent the collective opinion of a group of technical experts on the contribution of a patent in Drill Bit Topology to a series of higher level concepts.
- the cumulative knowledge may say that a single patent in Drill Bit Topology would contribute .22 patent-units toward a theoretical patent in Drill Bit Deposition, .24 patent-units toward a theoretical patent in Drill Bit Corrosion, and .27 patent- units toward a theoretical patent in Formation Penetration.
- Table 5 Fractional Contribution Matrix of Each Category to a Higher-Level Concept
- Drill Fluid Rheology 0 33 0 12 0 19 0 02 0 23 0 1 1
- Table 6 represents the summation of the matrix multiplication of these two matrices leading to the estimate of the number of theoretical patents in these higher level subjects.
- the number of theoretical patents in Drill Bit Deposition would be derived by multiplying column A, which represents the cumulative opinion of a group of technical experts (Table 5), by the number of patents in each category for each year (Table 4) and summing the contribution of each category to the theoretical number of patents in Drill Bit Deposition.
- Table 6 displays the derived count of patents in each of these higher-level, more abstract concepts, across a span of years.
- Table 7 represents the calculation of the theoretical number of patents in Drill Bit Deposition which would be represented by a set of patents. For each subject category from Table 4, the number of patents would be multiplied by the fractional contribution of that subject categoiy, from Table 5, Drill Bit Deposition in year 1982. The theoretical number of patents contributed by each category would be summed to arrive at a theoretical number of patents in Drill Bit Deposition in 1982.
- Figure 4 displays the data from Table 6 in a graphical display which allows the trends and discontinuities in the research patterns, represented by the count of theoretical patents, in the higher-level, more abstract subjects in Table 6, to be observed. These trends and discontinuities were previously hidden due to both the complexity and length of each patent and/or technical document in the set of documents under review, and also due to the complexity of the higher level concepts themselves. These higher level concepts can not be searched by use of an expert technical search (ETS) but rather must be derived from lower level concepts which can be searched using an expert technical search (ETS), using the methods of this invention.
- ETS expert technical search
Abstract
Description
Claims
Priority Applications (5)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
EP97929800A EP0979465A4 (en) | 1996-06-04 | 1997-06-04 | A relational database system containing a multidimensional hierarchical model of interrelated subject categories with recognition capabilities |
JP10500849A JP2000511668A (en) | 1996-06-04 | 1997-06-04 | A cognitive relational database system containing a multidimensional hierarchical model consisting of interrelated subject categories |
BR9710844A BR9710844A (en) | 1996-06-04 | 1997-06-04 | Computer readable medium that comprises a database system and process for creating a database |
AU33774/97A AU715248B2 (en) | 1996-06-04 | 1997-06-04 | A relational database system containing a multidimensional hierarchical model of interrelated subject categories with recognition capabilities |
NO985649A NO985649L (en) | 1996-06-04 | 1998-12-03 | Multi-dimensional database system |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US08/655,262 | 1996-06-04 | ||
US08/655,262 US5721910A (en) | 1996-06-04 | 1996-06-04 | Relational database system containing a multidimensional hierachical model of interrelated subject categories with recognition capabilities |
Publications (1)
Publication Number | Publication Date |
---|---|
WO1997046958A1 true WO1997046958A1 (en) | 1997-12-11 |
Family
ID=24628191
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/US1997/009729 WO1997046958A1 (en) | 1996-06-04 | 1997-06-04 | A relational database system containing a multidimensional hierarchical model of interrelated subject categories with recognition capabilities |
Country Status (8)
Country | Link |
---|---|
US (1) | US5721910A (en) |
EP (1) | EP0979465A4 (en) |
JP (1) | JP2000511668A (en) |
AU (1) | AU715248B2 (en) |
BR (1) | BR9710844A (en) |
CA (1) | CA2255880A1 (en) |
NO (1) | NO985649L (en) |
WO (1) | WO1997046958A1 (en) |
Cited By (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2006064382A3 (en) * | 2004-11-30 | 2006-09-21 | Cognos Inc | Reporting model generation within a multidimentional enterprise software system |
US7418438B2 (en) | 2004-11-30 | 2008-08-26 | International Business Machines Corporation | Automated default dimension selection within a multidimensional enterprise software system |
US7593955B2 (en) | 2004-11-30 | 2009-09-22 | International Business Machines Corporation | Generation of aggregatable dimension information within a multidimensional enterprise software system |
US7610300B2 (en) | 2004-11-30 | 2009-10-27 | International Business Machines Corporation | Automated relational schema generation within a multidimensional enterprise software system |
Families Citing this family (132)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US6339767B1 (en) * | 1997-06-02 | 2002-01-15 | Aurigin Systems, Inc. | Using hyperbolic trees to visualize data generated by patent-centric and group-oriented data processing |
US5991751A (en) * | 1997-06-02 | 1999-11-23 | Smartpatents, Inc. | System, method, and computer program product for patent-centric and group-oriented data processing |
US6963920B1 (en) * | 1993-11-19 | 2005-11-08 | Rose Blush Software Llc | Intellectual asset protocol for defining data exchange rules and formats for universal intellectual asset documents, and systems, methods, and computer program products related to same |
US6807558B1 (en) * | 1995-06-12 | 2004-10-19 | Pointcast, Inc. | Utilization of information “push” technology |
US6112201A (en) * | 1995-08-29 | 2000-08-29 | Oracle Corporation | Virtual bookshelf |
US6510435B2 (en) * | 1996-09-02 | 2003-01-21 | Rudolf Bayer | Database system and method of organizing an n-dimensional data set |
US6037944A (en) * | 1996-11-07 | 2000-03-14 | Natrificial Llc | Method and apparatus for displaying a thought network from a thought's perspective |
US6918096B2 (en) * | 1996-11-07 | 2005-07-12 | Thebrain Technologies, Corp. | Method and apparatus for displaying a network of thoughts from a thought's perspective |
US6073134A (en) * | 1997-05-29 | 2000-06-06 | Oracle Corporation | Method article of manufacture, and apparatus for generating a multi-dimensional record management index |
US6055540A (en) * | 1997-06-13 | 2000-04-25 | Sun Microsystems, Inc. | Method and apparatus for creating a category hierarchy for classification of documents |
US6098066A (en) * | 1997-06-13 | 2000-08-01 | Sun Microsystems, Inc. | Method and apparatus for searching for documents stored within a document directory hierarchy |
US5943668A (en) * | 1997-06-30 | 1999-08-24 | International Business Machines Corporation | Relational emulation of a multi-dimensional database |
US5905985A (en) * | 1997-06-30 | 1999-05-18 | International Business Machines Corporation | Relational database modifications based on multi-dimensional database modifications |
US6128617A (en) * | 1997-11-24 | 2000-10-03 | Lowry Software, Incorporated | Data display software with actions and links integrated with information |
US6282546B1 (en) | 1998-06-30 | 2001-08-28 | Cisco Technology, Inc. | System and method for real-time insertion of data into a multi-dimensional database for network intrusion detection and vulnerability assessment |
JP3856969B2 (en) * | 1998-11-02 | 2006-12-13 | 株式会社日立製作所 | Object analysis design support method |
US7966328B2 (en) | 1999-03-02 | 2011-06-21 | Rose Blush Software Llc | Patent-related tools and methodology for use in research and development projects |
US7716060B2 (en) | 1999-03-02 | 2010-05-11 | Germeraad Paul B | Patent-related tools and methodology for use in the merger and acquisition process |
JP2003527647A (en) * | 1999-04-08 | 2003-09-16 | オーリジン システムズ インコーポレイテッド | Patent-related tools and methodologies used in R & D projects |
US6853950B1 (en) * | 1999-07-20 | 2005-02-08 | Newsedge Corporation | System for determining changes in the relative interest of subjects |
US6408292B1 (en) | 1999-08-04 | 2002-06-18 | Hyperroll, Israel, Ltd. | Method of and system for managing multi-dimensional databases using modular-arithmetic based address data mapping processes on integer-encoded business dimensions |
US6385604B1 (en) * | 1999-08-04 | 2002-05-07 | Hyperroll, Israel Limited | Relational database management system having integrated non-relational multi-dimensional data store of aggregated data elements |
US6546395B1 (en) * | 1999-08-30 | 2003-04-08 | International Business Machines Corporation | Multi-dimensional restructure performance by selecting a technique to modify a relational database based on a type of restructure |
US6542895B1 (en) * | 1999-08-30 | 2003-04-01 | International Business Machines Corporation | Multi-dimensional restructure performance when adding or removing dimensions and dimensions members |
US20090259506A1 (en) * | 1999-09-14 | 2009-10-15 | Barney Jonathan A | Method and system for rating patents and other intangible assets |
US6556992B1 (en) * | 1999-09-14 | 2003-04-29 | Patent Ratings, Llc | Method and system for rating patents and other intangible assets |
US7016852B1 (en) | 1999-09-30 | 2006-03-21 | Eugene M. Lee | Fee transaction system and method for intellectual property acquisition and/or maintenance |
US6510420B1 (en) | 1999-09-30 | 2003-01-21 | International Business Machines Corporation | Framework for dynamic hierarchical grouping and calculation based on multidimensional member characteristics |
US7016851B1 (en) * | 1999-09-30 | 2006-03-21 | Eugene M. Lee | Systems and methods for preparation of an intellectual property filing in accordance with jurisdiction- and/or agent specific requirements |
US20090307577A1 (en) * | 2001-08-28 | 2009-12-10 | Lee Eugene M | System for providing a binding cost for foreign filing a patent application |
US20020138297A1 (en) * | 2001-03-21 | 2002-09-26 | Lee Eugene M. | Apparatus for and method of analyzing intellectual property information |
US20040103112A1 (en) * | 1999-10-08 | 2004-05-27 | Colson Thomas J. | Computer based method and apparatus for mining and displaying patent data |
US6405208B1 (en) * | 1999-12-13 | 2002-06-11 | Hyperion Solutions Corporation | Dynamic recursive build for multidimensional databases and methods and apparatus thereof |
US20070260974A1 (en) * | 1999-12-27 | 2007-11-08 | Hauser Carl H | System and method for assigning a disposition to a document through information flow knowledge |
US6675166B2 (en) | 2000-02-09 | 2004-01-06 | The John Hopkins University | Integrated multidimensional database |
US20020029207A1 (en) * | 2000-02-28 | 2002-03-07 | Hyperroll, Inc. | Data aggregation server for managing a multi-dimensional database and database management system having data aggregation server integrated therein |
JP4713707B2 (en) * | 2000-03-28 | 2011-06-29 | 日産自動車株式会社 | Data display system |
US20020077757A1 (en) * | 2000-04-03 | 2002-06-20 | Libraria, Inc. | Chemistry resource database |
US20020022974A1 (en) * | 2000-04-14 | 2002-02-21 | Urban Lindh | Display of patent information |
US7523114B2 (en) * | 2000-04-24 | 2009-04-21 | Ebay Inc. | Method and system for categorizing items in both actual and virtual categories |
US6915289B1 (en) | 2000-05-04 | 2005-07-05 | International Business Machines Corporation | Using an index to access a subject multi-dimensional database |
US7269786B1 (en) | 2000-05-04 | 2007-09-11 | International Business Machines Corporation | Navigating an index to access a subject multi-dimensional database |
US20020049707A1 (en) * | 2000-05-08 | 2002-04-25 | Townsley Norton R. | Expanded patent search |
US6446083B1 (en) * | 2000-05-12 | 2002-09-03 | Vastvideo, Inc. | System and method for classifying media items |
US7020679B2 (en) * | 2000-05-12 | 2006-03-28 | Taoofsearch, Inc. | Two-level internet search service system |
US20020019836A1 (en) * | 2000-05-16 | 2002-02-14 | Hirokazu Uchio | Information processing apparatus for management of documents relevant to patent application |
US6721729B2 (en) * | 2000-06-09 | 2004-04-13 | Thanh Ngoc Nguyen | Method and apparatus for electronic file search and collection |
US7058516B2 (en) * | 2000-06-30 | 2006-06-06 | Bioexpertise, Inc. | Computer implemented searching using search criteria comprised of ratings prepared by leading practitioners in biomedical specialties |
US7376635B1 (en) * | 2000-07-21 | 2008-05-20 | Ford Global Technologies, Llc | Theme-based system and method for classifying documents |
US20060161353A1 (en) * | 2000-07-24 | 2006-07-20 | Bioexpertise, Inc. | Computer implemented searching using search criteria comprised of ratings prepared by leading practitioners in biomedical specialties |
AU2001277082A1 (en) * | 2000-07-24 | 2002-02-05 | Protigen, Inc. | A method and system for a document search system using search criteria comprised of ratings prepared by experts |
KR100729779B1 (en) * | 2000-07-26 | 2007-06-20 | 삼성전자주식회사 | Method for analysing of an intellectual property information and system for performing the same |
US7493391B2 (en) * | 2001-02-12 | 2009-02-17 | International Business Machines Corporation | System for automated session resource clean-up by determining whether server resources have been held by client longer than preset thresholds |
US20050101012A1 (en) * | 2001-03-12 | 2005-05-12 | Gerold Schuler | CD4+CD25+ regulatory T cells from human blood |
US8484177B2 (en) | 2001-03-21 | 2013-07-09 | Eugene M. Lee | Apparatus for and method of searching and organizing intellectual property information utilizing a field-of-search |
US6665670B2 (en) | 2001-03-30 | 2003-12-16 | M.Cam, Inc. | Method and system for graphical representation of multitemporal, multidimensional data relationships |
US20020147738A1 (en) * | 2001-04-06 | 2002-10-10 | Reader Scot A. | Method and appratus for finding patent-relevant web documents |
EP1256883A1 (en) * | 2001-05-10 | 2002-11-13 | Siemens Aktiengesellschaft | Patent information system |
US6980984B1 (en) * | 2001-05-16 | 2005-12-27 | Kanisa, Inc. | Content provider systems and methods using structured data |
US20020178120A1 (en) * | 2001-05-22 | 2002-11-28 | Reid Zachariah J. | Contract generation and administration system |
US9541977B1 (en) | 2001-08-28 | 2017-01-10 | Eugene M. Lee | Computer-implemented method and system for automated claim charts with context associations |
US9460414B2 (en) | 2001-08-28 | 2016-10-04 | Eugene M. Lee | Computer assisted and/or implemented process and system for annotating and/or linking documents and data, optionally in an intellectual property management system |
US7885987B1 (en) | 2001-08-28 | 2011-02-08 | Lee Eugene M | Computer-implemented method and system for managing attributes of intellectual property documents, optionally including organization thereof |
US6920444B2 (en) * | 2001-09-26 | 2005-07-19 | Sun Microsystems, Inc. | Accessing relational database using an object-oriented language |
WO2003030033A2 (en) * | 2001-10-01 | 2003-04-10 | Delphion, Inc. | System and method for generating a work set of patents or other documents |
NZ540052A (en) * | 2001-10-17 | 2007-05-31 | Jorge Diniz Queiroga Loureiro | Data management |
EP1324235A1 (en) * | 2001-12-27 | 2003-07-02 | Sap Ag | Determination of a characteristic function of a matrix using a predetermined scheme |
EP1324236A1 (en) * | 2001-12-27 | 2003-07-02 | Sap Ag | Determination of a characteristic function of a matrix using accumulation and consolidation |
DE10215495A1 (en) * | 2002-04-09 | 2003-10-30 | Bayer Ag | Computer system and method for research, statistical evaluation and analysis of documents |
US20040025048A1 (en) * | 2002-05-20 | 2004-02-05 | Porcari Damian O. | Method and system for role-based access control to a collaborative online legal workflow tool |
US20040015481A1 (en) * | 2002-05-23 | 2004-01-22 | Kenneth Zinda | Patent data mining |
US20030229470A1 (en) * | 2002-06-10 | 2003-12-11 | Nenad Pejic | System and method for analyzing patent-related information |
US8222033B2 (en) | 2002-08-12 | 2012-07-17 | Argos Therapeutics, Inc. | CD4+CD25− T cells and Tr1-like regulatory T cells |
US20040230568A1 (en) * | 2002-10-28 | 2004-11-18 | Budzyn Ludomir A. | Method of searching information and intellectual property |
US7472127B2 (en) | 2002-12-18 | 2008-12-30 | International Business Machines Corporation | Methods to identify related data in a multidimensional database |
US20040181518A1 (en) * | 2003-03-14 | 2004-09-16 | Mayo Bryan Edward | System and method for an OLAP engine having dynamic disaggregation |
US20040236753A1 (en) * | 2003-05-20 | 2004-11-25 | Porcari Damian O. | Method and system for automated messaging in an online legal workflow tool |
US7333997B2 (en) * | 2003-08-12 | 2008-02-19 | Viziant Corporation | Knowledge discovery method with utility functions and feedback loops |
US20050278362A1 (en) * | 2003-08-12 | 2005-12-15 | Maren Alianna J | Knowledge discovery system |
US20050108384A1 (en) * | 2003-10-23 | 2005-05-19 | Lambert John R. | Analysis of message sequences |
US8694419B2 (en) * | 2003-11-18 | 2014-04-08 | Ocean Tomo, Llc | Methods and systems for utilizing intellectual property assets and rights |
US20050198026A1 (en) * | 2004-02-03 | 2005-09-08 | Dehlinger Peter J. | Code, system, and method for generating concepts |
WO2005086039A2 (en) * | 2004-03-04 | 2005-09-15 | Bayer Business Services Gmbh | Method for the provision of any type of storage media containing pre-recorded structured information |
WO2005114468A2 (en) * | 2004-05-20 | 2005-12-01 | Wizpatent, Pte Ltd. | System and method for text segmentation and display |
US20060036451A1 (en) | 2004-08-10 | 2006-02-16 | Lundberg Steven W | Patent mapping |
US7840460B2 (en) * | 2004-08-11 | 2010-11-23 | Allan Williams | System and method for patent portfolio evaluation |
US8145640B2 (en) * | 2004-08-11 | 2012-03-27 | Allan Williams | System and method for patent evaluation and visualization of the results thereof |
US8145639B2 (en) * | 2004-08-11 | 2012-03-27 | Allan Williams | System and methods for patent evaluation |
US8161049B2 (en) * | 2004-08-11 | 2012-04-17 | Allan Williams | System and method for patent evaluation using artificial intelligence |
US20060036453A1 (en) * | 2004-08-11 | 2006-02-16 | Allan Williams | Bias compensated method and system for patent evaluation |
US7389282B2 (en) * | 2004-11-02 | 2008-06-17 | Viziant Corporation | System and method for predictive analysis and predictive analysis markup language |
US7536312B2 (en) * | 2005-01-26 | 2009-05-19 | Ocean Tomo, Llc | Method of appraising and insuring intellectual property |
US7747648B1 (en) * | 2005-02-14 | 2010-06-29 | Yahoo! Inc. | World modeling using a relationship network with communication channels to entities |
WO2006110853A2 (en) * | 2005-04-12 | 2006-10-19 | Maren Alianna J | System and method for evidence accumulation and hypothesis generation |
US7958120B2 (en) | 2005-05-10 | 2011-06-07 | Netseer, Inc. | Method and apparatus for distributed community finding |
US9110985B2 (en) * | 2005-05-10 | 2015-08-18 | Neetseer, Inc. | Generating a conceptual association graph from large-scale loosely-grouped content |
WO2006128183A2 (en) | 2005-05-27 | 2006-11-30 | Schwegman, Lundberg, Woessner & Kluth, P.A. | Method and apparatus for cross-referencing important ip relationships |
WO2007014341A2 (en) | 2005-07-27 | 2007-02-01 | Schwegman, Lundberg & Woessner, P.A. | Patent mapping |
WO2007027967A2 (en) * | 2005-08-31 | 2007-03-08 | Eagleforce Associates | System for hypothesis generation |
US7716226B2 (en) | 2005-09-27 | 2010-05-11 | Patentratings, Llc | Method and system for probabilistically quantifying and visualizing relevance between two or more citationally or contextually related data objects |
US20070168345A1 (en) * | 2006-01-17 | 2007-07-19 | Andrew Gibbs | System and method of identifying subject matter experts |
US8825657B2 (en) | 2006-01-19 | 2014-09-02 | Netseer, Inc. | Systems and methods for creating, navigating, and searching informational web neighborhoods |
EP1920366A1 (en) | 2006-01-20 | 2008-05-14 | Glenbrook Associates, Inc. | System and method for context-rich database optimized for processing of concepts |
US20080097773A1 (en) * | 2006-02-06 | 2008-04-24 | Michael Hill | Non-disclosure bond for deterring unauthorized disclosure and other misuse of intellectual property |
WO2007100923A2 (en) * | 2006-02-28 | 2007-09-07 | Ilial, Inc. | Methods and apparatus for visualizing, managing, monetizing and personalizing knowledge search results on a user interface |
DE102007008904A1 (en) * | 2006-05-08 | 2007-11-15 | Abb Technology Ag | System and method for the automated and structured transfer of technical documents and the management of the acquired documents in a database |
US9817902B2 (en) * | 2006-10-27 | 2017-11-14 | Netseer Acquisition, Inc. | Methods and apparatus for matching relevant content to user intention |
JP2008112934A (en) * | 2006-10-31 | 2008-05-15 | Oki Electric Ind Co Ltd | Semiconductor memory, and its manufacturing method |
US7730017B2 (en) * | 2007-03-30 | 2010-06-01 | Google Inc. | Open profile content identification |
US8321462B2 (en) * | 2007-03-30 | 2012-11-27 | Google Inc. | Custodian based content identification |
US20080243607A1 (en) * | 2007-03-30 | 2008-10-02 | Google Inc. | Related entity content identification |
US7983927B2 (en) | 2007-07-31 | 2011-07-19 | Peer Fusion Llc | System and method of managing community based and content based information networks |
US10387892B2 (en) | 2008-05-06 | 2019-08-20 | Netseer, Inc. | Discovering relevant concept and context for content node |
US20090300009A1 (en) * | 2008-05-30 | 2009-12-03 | Netseer, Inc. | Behavioral Targeting For Tracking, Aggregating, And Predicting Online Behavior |
US20100131513A1 (en) | 2008-10-23 | 2010-05-27 | Lundberg Steven W | Patent mapping |
JP2010231564A (en) * | 2009-03-27 | 2010-10-14 | Nomura Research Institute Ltd | Patent application evaluation device |
US9110971B2 (en) * | 2010-02-03 | 2015-08-18 | Thomson Reuters Global Resources | Method and system for ranking intellectual property documents using claim analysis |
AU2010202901B2 (en) | 2010-07-08 | 2016-04-14 | Patent Analytics Holding Pty Ltd | A system, method and computer program for preparing data for analysis |
US8639695B1 (en) | 2010-07-08 | 2014-01-28 | Patent Analytics Holding Pty Ltd | System, method and computer program for analysing and visualising data |
JP5195948B2 (en) * | 2011-02-07 | 2013-05-15 | 日産自動車株式会社 | Data display system |
WO2012112149A1 (en) * | 2011-02-16 | 2012-08-23 | Hewlett-Packard Development Company, L.P. | Population category hierarchies |
US9904726B2 (en) | 2011-05-04 | 2018-02-27 | Black Hills IP Holdings, LLC. | Apparatus and method for automated and assisted patent claim mapping and expense planning |
US20130086033A1 (en) | 2011-10-03 | 2013-04-04 | Black Hills Ip Holdings, Llc | Systems, methods and user interfaces in a patent management system |
US20130086070A1 (en) | 2011-10-03 | 2013-04-04 | Steven W. Lundberg | Prior art management |
EP2698753A1 (en) * | 2012-08-16 | 2014-02-19 | Corporación Medichem, S.L. | Data management system for generating a report document by linking technical data to intellectual property rights data |
US11461862B2 (en) | 2012-08-20 | 2022-10-04 | Black Hills Ip Holdings, Llc | Analytics generation for patent portfolio management |
US10311085B2 (en) | 2012-08-31 | 2019-06-04 | Netseer, Inc. | Concept-level user intent profile extraction and applications |
US9767190B2 (en) | 2013-04-23 | 2017-09-19 | Black Hills Ip Holdings, Llc | Patent claim scope evaluator |
US20150269263A1 (en) * | 2014-03-24 | 2015-09-24 | Computer Software Associates, Inc. | Method, system, and program product for creating reports for intellectual property |
JP6491345B2 (en) * | 2015-09-25 | 2019-03-27 | 株式会社日本電気特許技術情報センター | Information processing apparatus, information processing method, and program |
JP6347775B2 (en) | 2015-12-28 | 2018-06-27 | 日東電工株式会社 | Spiral membrane element |
US11640504B2 (en) | 2019-05-17 | 2023-05-02 | Samsung Electronics Co., Ltd. | Electronic apparatus and controlling method thereof |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5142674A (en) * | 1988-03-08 | 1992-08-25 | International Business Machines Corporation | Interchange object data base index which eliminates the need for private copies of interchange documents files by a plurality of application programs |
US5283894A (en) * | 1986-04-11 | 1994-02-01 | Deran Roger L | Lockless concurrent B-tree index meta access method for cached nodes |
US5511186A (en) * | 1992-11-18 | 1996-04-23 | Mdl Information Systems, Inc. | System and methods for performing multi-source searches over heterogeneous databases |
Family Cites Families (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CA2039365C (en) * | 1991-03-28 | 2000-01-18 | T. Dora Velissaropoulos | Method and means for encoding storing and retrieving hierarchical data processing information for a computer system |
FR2698977B1 (en) * | 1992-12-03 | 1994-12-30 | Alsthom Cge Alcatel | Multimedia information system. |
US5615112A (en) * | 1993-01-29 | 1997-03-25 | Arizona Board Of Regents | Synthesized object-oriented entity-relationship (SOOER) model for coupled knowledge-base/database of image retrieval expert system (IRES) |
US5594837A (en) * | 1993-01-29 | 1997-01-14 | Noyes; Dallas B. | Method for representation of knowledge in a computer as a network database system |
WO1995004960A2 (en) * | 1993-08-02 | 1995-02-16 | Persistence Software, Inc. | Method and apparatus for managing relational data in an object cache |
US5630125A (en) * | 1994-05-23 | 1997-05-13 | Zellweger; Paul | Method and apparatus for information management using an open hierarchical data structure |
JP2777698B2 (en) * | 1994-07-28 | 1998-07-23 | 日本アイ・ビー・エム株式会社 | Information retrieval system and method |
-
1996
- 1996-06-04 US US08/655,262 patent/US5721910A/en not_active Expired - Lifetime
-
1997
- 1997-06-04 CA CA002255880A patent/CA2255880A1/en not_active Abandoned
- 1997-06-04 JP JP10500849A patent/JP2000511668A/en not_active Ceased
- 1997-06-04 AU AU33774/97A patent/AU715248B2/en not_active Ceased
- 1997-06-04 BR BR9710844A patent/BR9710844A/en not_active Application Discontinuation
- 1997-06-04 EP EP97929800A patent/EP0979465A4/en not_active Withdrawn
- 1997-06-04 WO PCT/US1997/009729 patent/WO1997046958A1/en not_active Application Discontinuation
-
1998
- 1998-12-03 NO NO985649A patent/NO985649L/en not_active Application Discontinuation
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5283894A (en) * | 1986-04-11 | 1994-02-01 | Deran Roger L | Lockless concurrent B-tree index meta access method for cached nodes |
US5142674A (en) * | 1988-03-08 | 1992-08-25 | International Business Machines Corporation | Interchange object data base index which eliminates the need for private copies of interchange documents files by a plurality of application programs |
US5511186A (en) * | 1992-11-18 | 1996-04-23 | Mdl Information Systems, Inc. | System and methods for performing multi-source searches over heterogeneous databases |
Non-Patent Citations (1)
Title |
---|
See also references of EP0979465A4 * |
Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2006064382A3 (en) * | 2004-11-30 | 2006-09-21 | Cognos Inc | Reporting model generation within a multidimentional enterprise software system |
US7418438B2 (en) | 2004-11-30 | 2008-08-26 | International Business Machines Corporation | Automated default dimension selection within a multidimensional enterprise software system |
US7505888B2 (en) | 2004-11-30 | 2009-03-17 | International Business Machines Corporation | Reporting model generation within a multidimensional enterprise software system |
US7593955B2 (en) | 2004-11-30 | 2009-09-22 | International Business Machines Corporation | Generation of aggregatable dimension information within a multidimensional enterprise software system |
US7610300B2 (en) | 2004-11-30 | 2009-10-27 | International Business Machines Corporation | Automated relational schema generation within a multidimensional enterprise software system |
US8131533B2 (en) | 2004-11-30 | 2012-03-06 | International Business Machines Corporation | Reporting model generation within a multidimensional enterprise software system |
US9639814B2 (en) | 2004-11-30 | 2017-05-02 | International Business Machines Corporation | Automated default dimension selection within a multidimensional enterprise software system |
Also Published As
Publication number | Publication date |
---|---|
NO985649D0 (en) | 1998-12-03 |
NO985649L (en) | 1999-01-27 |
AU715248B2 (en) | 2000-01-20 |
BR9710844A (en) | 1999-08-17 |
JP2000511668A (en) | 2000-09-05 |
AU3377497A (en) | 1998-01-05 |
EP0979465A4 (en) | 2000-10-11 |
EP0979465A1 (en) | 2000-02-16 |
US5721910A (en) | 1998-02-24 |
CA2255880A1 (en) | 1997-12-11 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
AU715248B2 (en) | A relational database system containing a multidimensional hierarchical model of interrelated subject categories with recognition capabilities | |
CN106202248B (en) | Phrase-based search in information retrieval system | |
US9710457B2 (en) | Computer-implemented patent portfolio analysis method and apparatus | |
Eom | Author Cocitation Analysis: Quantitative Methods for Mapping the Intellectual Structure of an Academic Discipline: Quantitative Methods for Mapping the Intellectual Structure of an Academic Discipline | |
CN101408885B (en) | Modeling topics using statistical distributions | |
EP1899800B1 (en) | Schema and etl tools for structured and unstructured data | |
Matignon | Data mining using SAS enterprise miner | |
EP1899855B1 (en) | System and method of making unstructured data available to structured data analysis tools | |
EP1618496B1 (en) | A system and method for generating refinement categories for a set of search results | |
US20060179051A1 (en) | Methods and apparatus for steering the analyses of collections of documents | |
US20040015481A1 (en) | Patent data mining | |
US20070011183A1 (en) | Analysis and transformation tools for structured and unstructured data | |
CN101408886A (en) | Selecting tags for a document by analyzing paragraphs of the document | |
US20080124686A1 (en) | Skill-set identification | |
US20050114302A1 (en) | Method for fast searching and displaying a genealogical tree of patents from a patent database | |
Hilderman et al. | Mining association rules from market basket data using share measures and characterized itemsets | |
Wang et al. | Hybrid rule ordering in classification association rule mining | |
Feldman et al. | Pattern based browsing in document collections | |
Imberman | Effective use of the kdd process and data mining for computer performance professionals | |
CN114817265B (en) | Financial information acquisition method by utilizing big data server | |
Gorla et al. | Is the lack of keyword synergism inhibiting maturation in the MIS theory? An exploratory perspective | |
Sumathi et al. | Data mining and data warehousing | |
Saikia et al. | Study of Association Rule Mining And different hiding Techniques | |
Karanikas et al. | A temporal text mining application in competitive intelligence | |
EP1643379B1 (en) | Document searching system |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AK | Designated states |
Kind code of ref document: A1 Designated state(s): AL AU BA BB BG BR CA CN CU CZ EE GE HU IL IS JP KP KR LC LK LR LT LV MG MK MN MX NO NZ PL RO SG SI SK TR TT UA UZ VN YU AM AZ BY KG KZ MD RU TJ TM |
|
AL | Designated countries for regional patents |
Kind code of ref document: A1 Designated state(s): GH KE LS MW SD SZ UG AT BE CH DE DK ES FI FR GB GR IE IT LU MC NL PT SE BF BJ CF CG CI CM GA GN ML MR NE SN TD TG |
|
DFPE | Request for preliminary examination filed prior to expiration of 19th month from priority date (pct application filed before 20040101) | ||
121 | Ep: the epo has been informed by wipo that ep was designated in this application | ||
ENP | Entry into the national phase |
Ref document number: 2255880 Country of ref document: CA Ref country code: CA Ref document number: 2255880 Kind code of ref document: A Format of ref document f/p: F |
|
WWE | Wipo information: entry into national phase |
Ref document number: 1997929800 Country of ref document: EP |
|
WWP | Wipo information: published in national office |
Ref document number: 1997929800 Country of ref document: EP |
|
WWW | Wipo information: withdrawn in national office |
Ref document number: 1997929800 Country of ref document: EP |