CONTENT IDENTIFICATION AND CLASSIFICATION APPARATUS, SYSTEMS, AND METHODS

• US 20090055242A1
• Filed: 08/24/2007
• Published: 02/26/2009
• Est. Priority Date: 08/24/2007
• Status: Abandoned Application

• Current Assignee: Ignite Firstrain Solutions, Inc.
• Original Assignee: Ignite Firstrain Solutions, Inc.
• Inventors: Gandham, Sailesh Kumar Das, Bhatia, Ranjeet S., Prospero, Michael D., Warikoo, Abhimanyu, Rewari, Gaurav, Sahasrabudhe, Sadanand, Yu, Xiang, Cooke, David
• Application Number:
  US11/844,796
• Publication Number:
  US 20090055242A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0205 Location or geographical consideration

Abstract

Embodiments herein relate market entities, market topics, and market relationships in a market relationship module (MRM). The MRM is used to index individually relevant information content and to formulate queries for later retrieval and presentation of the relevant content. Other embodiments are described and claimed.

Claims

1. An apparatus, comprising:

a market relationship module (MRM) including a market entity dataset, a market topic dataset, a market relationship dataset, and a set of semantic rules, the MRM to relate at least one of a plurality of market entities, a plurality of market topics, or at least one market entity and at least one market topic according to at least one market relationship;

a content processor coupled to the MRM to receive unstructured information content and to parse the unstructured information content into a plurality of selected content segments, each selected content segment related to at least one of a selected market entity, a selected market topic, or a keyword, wherein selected content segments related to the selected market entity and to the selected market topic are parsed according to the MRM, and to index a location identifier associated with the selected content segment by at least one of an identifier associated with the selected market entity, an identifier associated with the selected market topic, or the keyword; and

a master index coupled to the content processor to store the indexed location identifier and at least one of the identifier associated with the selected market entity, the identifier associated with the selected market topic, or the keyword.

2. The apparatus of claim 1, wherein the MRM comprises at least one of a relational database, an eXtensible Markup Language (XML) schema, an object oriented database, a semantic database, or a resource description framework (RDF) data store.

3. The apparatus of claim 1, wherein the at least one market relationship comprises a dynamic market relationship.

4. The apparatus of claim 1, wherein the MRM is configured to store a dynamic market relationship established in response to a market event after initially loading the MRM.

5. The apparatus of claim 1, wherein the MRM is configured to store a dynamic market relationship established if a frequency of coincidence between at least one of two market entities, two market topics, or a market entity and a market topic found in at least one of the plurality of selected content segments increases past a selected threshold.

6. The apparatus of claim 1, wherein the MRM is configured to store a new market topic synthesized from at least one of the plurality of market topics or the at least one market entity and the at least one market topic and wherein at least one of the plurality of market topics or the at least one market entity and the at least one market topic is provided at query time.

7. The apparatus of claim 1, wherein the MRM is configured to store a new market entity synthesized from at least one of the plurality of market entities or the at least one market entity and the at least one market topic and wherein at least one of the plurality of market topics or the at least one market entity and the at least one market topic is provided at query time.

8. The apparatus of claim 1, wherein each selected content segment comprises at least one of a content file, a portion of the content file, a tag associated with the content file, or a result of a translation operation performed on the content file.

9. The apparatus of claim 8, wherein the content file comprises at least one of a markup language page, a text file, a word processing file, a graphics file, a video file, an audio file, a spreadsheet file, a slide presentation file, or a page description file.

10. The apparatus of claim 1, wherein the content processor is configured to extract the selected content segment from at least one of an internet, an intranet, a database, a library, or a content stream.

11. The apparatus of claim 1, wherein the content processor is configured to receive the selected content segment from at least one of a linked content crawling engine or a content stream filter.

12. The apparatus of claim 1, wherein the location identifier associated with each selected content segment comprises at least one of a uniform resource locator (URL), a file location, or a location of a portion of a file within the file.

13. The apparatus of claim 1, further comprising:

an MRM administrative graphical user interface (GUI) communicatively coupled to the MRM to receive the market entity dataset, the market topic dataset, the market relationship dataset, and the set of semantic rules.

14. The apparatus of claim 1, further comprising:

a market entity loading module coupled to the MRM to load the market entity dataset and a subset of semantic rules associated with a plurality of market entity representations contained in the market entity dataset;

a market topic loading module coupled to the MRM to load the market topic dataset and a subset of semantic rules associated with a plurality of market topic representations contained in the market topic dataset; and

a market relationship loading module coupled to the MRM to load the market relationship dataset.

15. The apparatus of claim 1, further comprising:

an MRM loading application programming interface (API) to load at least one of the market entity dataset, the market topic dataset, the market relationship dataset, or the set of semantic rules from an interprocess communications source.

16. The apparatus of claim 1, wherein the content processor is configured to associate at least one content segment offset with each selected market entity, selected market topic, or keyword, and wherein the at least one content segment offset corresponds to a position of an occurrence of the selected market entity, selected market topic, or keyword within the selected content segment.

17. The apparatus of claim 16, wherein the at least one content segment offset comprises at least one of a position of a word, a position of a sentence, a position of a paragraph, or a position of a section of the selected content segment.

18. The apparatus of claim 1, wherein the master index comprises a keyword index, a market entity index, and a market topic index.

19. The apparatus of claim 18, wherein each entry within the keyword index comprises at least one of a keyword, a keyphrase, a corresponding content location identifier, and at least one content segment offset, wherein the keyword or keyphrase is extracted from at least one of the plurality of selected content segments, and wherein each of the plurality of selected content segments is located at a content location corresponding to an associated content location identifier.

20. The apparatus of claim 18, further including:

a keyword association metric value stored in the keyword index, the keyword association metric value calculated based upon at least one of a frequency of occurrence of the keyword in the selected content segment, a presence of the keyword in a headline associated with the selected content segment, an occurrence of the keyword with greater prominence than surrounding text, an occurrence of the keyword in a caption associated with a picture found within the selected content segment, or a presence of the keyword in anchor text.

21. The apparatus of claim 18, wherein each entry within the market entity index comprises at least one of a market entity identifier, a corresponding content location identifier, and at least one content segment offset, wherein the market entity identifier corresponds to a market entity selected using the MRM and referred to by at least one of the plurality of selected content segments, and wherein each of the plurality of selected content segments is located at a content location corresponding to an associated content location identifier.

22. The apparatus of claim 18, wherein each entry within the market topic index comprises at least one of a market topic identifier, a corresponding content location identifier, and at least one content segment offset, wherein the market topic identifier corresponds to a market topic selected using the MRM and referred to by at least one of the plurality of selected content segments, and wherein each of the plurality of selected content segments is located at a content location corresponding to an associated content location identifier.

23. The apparatus of claim 1, wherein the master index is configured to store a strength-of-association metric value corresponding to at least one of the selected market entity or the selected market topic, the strength-of-association metric value to indicate relatedness between the selected market entity and the selected content segment or the selected market topic and the selected content segment, wherein the strength-of-association metric value is computed using the set of semantic rules and is based upon at least one of a frequency of occurrence of at least one keyword indicative of the market entity or the market topic in the selected content segment, a presence of the at least one keyword in a headline associated with the selected content segment, an occurrence of the at least one keyword with greater prominence than surrounding text, an occurrence of the at least one keyword in a caption associated with a picture found within the selected content segment, or a presence of the at least one keyword in anchor text.

24. The apparatus of claim 1, wherein the master index is configured to store an impact metric value associated with at least one of an impacted market entity or an impacted market topic, the impact metric value to indicate a relative importance of the selected content segment to the impacted market entity or the impacted market topic, wherein the impact metric value is calculated using the set of semantic rules and comprises a composite score based upon at least one of a pre-defined assessment of a financial impact of an impacting market entity or market topic found in the selected content segment on the impacted market entity or on the impacted market topic, an occurrence in the selected content segment of an impacting market entity pre-defined as high impact, an occurrence in the selected content segment of an impacting market topic pre-defined as high impact, an occurrence in the selected content segment of an impacting market entity-keyword pair, wherein the impacting market entity-keyword pair is pre-defined as high impact, an occurrence in the selected content segment of an impacting market topic-keyword pair wherein the impacting market-topic keyword pair is predefined as high impact, an occurrence in the selected content segment of multiple key market entities, an occurrence in the selected content segment of multiple key market topics, or authorship of the selected content segment by a member of a predefined list of individuals determined through research to be at least one of a member of management, a thought leader, or an influential person in an industry.

25. The apparatus of claim 1, further comprising:

a linked content crawling engine coupled to the content processor to navigate among a plurality of linked content sources, to extract a crawled plurality of content segments from the plurality of linked content sources, and to present the crawled plurality of content segments to the content processor.

26. The apparatus of claim 1, further comprising:

a content stream filter coupled to the content processor to extract a filtered plurality of content segments and to present the filtered plurality of content segments to the content processor.

27. A system, comprising:

a market relationship module (MRM) including a market entity dataset, a market topic dataset, a market relationship dataset, and a set of semantic rules, the MRM to relate at least one of a plurality of market entities, a plurality of market topics, or at least one market entity and at least one market topic according to at least one market relationship;

a content processor coupled to the MRM to receive unstructured information content and to parse the unstructured information content into a plurality of selected content segments, each selected content segment related to at least one of a selected market entity, a selected market topic, or a keyword, wherein the selected content segments related to the selected market entity and to the selected market topic are parsed according to the MRM, and to index a location identifier associated with the selected content segment by at least one of an identifier associated with the selected market entity, an identifier associated with the selected market topic, or the keyword;

a master index coupled to the content processor to store the indexed location identifier and at least one of the identifier associated with the selected market entity, the identifier associated with the selected market topic, or the keyword; and

an MRM feedback module communicatively coupled to the MRM to modify the MRM according to at least one of feedback data derived from content retrieval operations using the MRM, user feedback based upon a result of the retrieval operations using the MRM, at least one market event, or at least one market research data point.

28. A method, comprising:

relating at least one of a plurality of market entities, a plurality of market topics, or at least one market entity and at least one market topic according to at least one market relationship in a market relationship module (MRM).

29. The method of claim 28, wherein each of the plurality of market entities comprises at least one of a company, a subsidiary, a joint venture, a product brand, a service brand, a product application, a service application, a non-profit organization, an advocacy group, a region, a governmental sub-division, a person, a raw material, or a component.

30. The method of claim 28, wherein each of the plurality of market entities comprises at least one of a plant or a location associated with at least one of a company, a subsidiary, a joint venture, a product brand, a service brand, a product application, a service application, a non-profit organization, an advocacy group, a region, or a governmental sub-division.

31. The method of claim 28, wherein each of the plurality of market topics comprises at least one of a geo-political market topic, a financial market topic, a corporate market topic, a macroeconomic market topic, a regulatory market topic, or a thematic market topic.

32. The method of claim 28, wherein the market relationship comprises at least one of customer, competitor, supplier, partner, subsidiary, parent company, merger and acquisition target, investor, regulator, banker, financier, employee, labor, lobbying group, advocacy group, industry consortium, union, management team member, director, thought leader, financial analyst, industry analyst, division, office, plant, producer, seller, development resource, embedded resource, place of operation, key market, or location of unit.

33. The method of claim 28, further comprising:

selectively establishing the market relationship as at least one of unidirectional or bidirectional.

34. The method of claim 28, further comprising:

selecting a first set of companies corresponding to an industry using a standard industry classification system;

narrowing the first set of companies to a second set of companies, wherein the second set of companies share a common market theme;

adding a company classified under a different industry to the second set of companies if the company classified under the other industry shares the common market theme; and

adding an unclassified company to the second set of companies if the unclassified company shares the common market theme.

35. The method of claim 28, further comprising:

creating a user-personalized MRM as a subset of the MRM.

36. The method of claim 28, further comprising:

receiving a set of market entity data; and

loading a market entity dataset associated with the MRM with the set of market entity data.

37. The method of claim 28, further comprising:

receiving a set of market topic data; and

loading a market topic dataset associated with the MRM with the set of market topic data.

38. The method of claim 28, further comprising:

receiving a set of market relationship data; and

loading a market relationship dataset associated with the MRM with the set of market relationship data.

39. The method of claim 28, further comprising:

receiving a set of semantic rules; and

loading the set of semantic rules into the MRM.

40. The method of claim 28, further comprising:

modifying the MRM according to at least one of feedback data derived from content extraction operations using the MRM, user feedback based upon extraction operations using the MRM, at least one market event, or at least one market research data point.

41. A method, comprising:

receiving unstructured information content;

parsing the unstructured information content into a plurality of selected content segments; and

relating each of the plurality of selected content segments to at least one of a selected market entity, a selected market topic, or a keyword, the selected content segments related to the selected market entity and to the selected market topic using an MRM.

42. The method of claim 41, further comprising:

indexing a location identifier associated with at least one of the plurality of selected content segments by at least one of an identifier associated with the selected market entity, an identifier associated with the selected market topic, or the keyword; and

storing the indexed location identifier associated with the at least one selected content segment in a master index.

43. The method of claim 42, further comprising:

formulating a query;

executing the query against at least one of the master index and the MRM;

receiving at least one returned content location identifier in response to the query;

retrieving at least one of a content segment, a market entity identifier, a market topic identifier, or a market relationship identifier; and

presenting the at least one of a content segment, a market entity identifier, a market topic identifier, or a market relationship identifier to a user.

44. The method of claim 41, further including:

associating at least one content segment offset with each selected market entity, selected market topic, or keyword, wherein the at least one content segment offset corresponds to a position of an occurrence of the selected market entity, selected market topic, or keyword within the selected content segment; and

storing the at least one content segment offset in a master index.

45. The method of claim 44, wherein the at least one content segment offset comprises at least one of a position of a word, a position of a sentence, a position of a paragraph, or a position of a section of the selected content segment.

46. The method of claim 41, further including:

calculating a strength-of-association metric value corresponding to at least one of the selected market entity or the selected market topic, the strength-of-association metric value to indicate relatedness between the selected market entity and the selected content segment or the selected market topic and the selected content segment; and

storing the strength-of-association metric value in a master index.

47. The method of claim 46, wherein the strength-of-association metric value is computed using a set of semantic rules and is based upon at least one of a frequency of occurrence of at least one keyword indicative of the market entity or the market topic in the selected content segment, a presence of the at least one keyword in a headline associated with the selected content segment, an occurrence of the at least one keyword with greater prominence than surrounding text, an occurrence of the at least one keyword in a caption associated with a picture found within the selected content segment, or a presence of the at least one keyword in anchor text.

48. The method of claim 41, further including:

calculating an impact metric value associated with at least one of an impacted market entity or an impacted market topic, wherein the impact metric value indicates a relative importance of the selected content segment to the impacted market entity or the impacted market topic; and

storing the impact metric value in a master index.

49. The method of claim 48, wherein the master index is configured to store an impact metric value associated with at least one of an impacted market entity or an impacted market topic, the impact metric value to indicate a relative importance of the selected content segment to the impacted market entity or the impacted market topic, wherein the impact metric value is calculated using a set of semantic rules and comprises a composite score based upon at least one of a pre-defined assessment of a financial impact of an impacting market entity or market topic found in the selected content segment on the impacted market entity or on the impacted market topic, an occurrence in the selected content segment of an impacting market entity pre-defined as high impact, an occurrence in the selected content segment of an impacting market topic pre-defined as high impact, an occurrence in the selected content segment of an impacting market entity-keyword pair, wherein the impacting market entity-keyword pair is pre-defined as high impact, an occurrence in the selected content segment of an impacting market topic-keyword pair wherein the impacting market-topic keyword pair is predefined as high impact, an occurrence in the selected content segment of multiple key market entities, an occurrence in the selected content segment of multiple key market topics, or authorship of the selected content segment by a member of a predefined list of individuals determined through research to be at least one of a member of management, a thought leader, or an influential person in an industry.

50. The method of claim 41, further comprising:

calculating a keyword association metric value, wherein the keyword association metric value is based upon at least one of a frequency of occurrence of the keyword in the selected content segment, a presence of the keyword in a headline associated with the selected content segment, an occurrence of the keyword with greater prominence than surrounding text, an occurrence of the keyword in a caption associated with a picture found within the selected content segment, or a presence of the keyword in anchor text; and

storing the keyword association metric value in the keyword index.

51. The method of claim 41, further comprising:

navigating among a plurality of linked content sources; and

extracting a plurality of content segments from the plurality of linked content sources using a linked content crawling engine.

52. The method of claim 41, further comprising:

filtering a content stream to extract a plurality of content segments; and

presenting the plurality of content segments as a set of unstructured information content.

53. A computer-readable medium having instructions, wherein the instructions, when executed, result in at least one processor performing:

relating at least one of a plurality of market entities, a plurality of market topics, or at least one market entity and at least one market topic according to at least one market relationship to create a market relationship module (MRM);

receiving unstructured information content; and

parsing the unstructured information content into a plurality of selected content segments according to the MRM, each of the plurality of selected content segments related to at least one of a selected market entity, a selected market topic, or a keyword.

54. The computer-readable medium of claim 53, wherein the instructions, when executed, result in the at least one processor performing:

indexing a location identifier associated with at least one selected content segment by at least one of an identifier associated with the selected market entity, an identifier associated with the selected market topic, or the keyword; and

storing the indexed location identifier associated with the at least one selected content segment in a master index.

55. The computer-readable medium of claim 54, wherein the instructions, when executed, result in the at least one processor performing:

formulating a query;

executing the query against at least one of the master index and the MRM;

receiving at least one returned content location identifier in response to the query;

retrieving at least one of a content segment, a market entity identifier, a market topic identifier, or a market relationship identifier; and

presenting the at least one of a content segment, a market entity identifier, a market topic identifier, or a market relationship identifier to a user.