Method, apparatus and computer program for managing the processing of extracted data

• US 20080301120A1
• Filed: 06/04/2007
• Published: 12/04/2008
• Est. Priority Date: 06/04/2007
• Status: Abandoned Application

• Current Assignee: Precipia Systems Incorporated
• Original Assignee: Precipia Systems Incorporated
• Inventors: Barney, Roger, Zhu, Jin
• Application Number:
  US11/806,833
• Publication Number:
  US 20080301120A1
• Time in Patent Office: Days
• US Class Current: 707/5
• CPC Class Codes: G06F 16/31 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/34 Browsing; Visualisation therefor
• CPC Class Codes: G06F 16/382 using citations hypermedia G06F16/94
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes

Abstract

Data is processed at a central data processor using multiple processing steps. The data is processed for the extraction of entities. Relationships between the extracted entities are also extracted. A system map is built using one or more factors derived from the extracted entities and relationships and organized by influence relationships. Each factor is associated with one or more options.

Claims

1. A central data processor, comprising:

at least one data processing module configured to process data, the data processing modules comprising;

an entity extraction module configured to extract entities from the data;

a network extraction module configured to communicate with the entity extraction module and to extract relationships between two or more entities extracted by the entity extraction module; and

a scenario building module for building a system map, each system map comprising one or more factors and one or more influence relationships between the one or more factors, the factors being derived from the extracted entities and relationships, each factor being associated with one or more options.

2. The central data processor of claim 1, wherein a plurality of the factors are selected from the extracted entities.

3. The central data processor of claim 1, further comprising a searching module for retrieving a representation of the data in response to a search request.

4. The central data processor of claim 3, wherein the search request is initiated by a host computer.

5. The central data processor of claim 3, wherein the search request is initiated by the central data processor.

6. The central data processor of claim 1, further comprising a memory for storing the extracted entities and the extracted relationships.

7. The central data processor of claim 1, wherein the at least one data processing module further comprises a timeline extraction module configured to extract time information from the data and to identify time-based relationships between entities.

8. The central data processor of claim 1, wherein the at least one data processing module further comprises a temporal analysis module configured to extract time information from the data.

9. The central data processor of claim 1, wherein the at least one data processing module further comprises a cross-reference module in communication with the entity extraction means and configured to extract entities from a subset of the data from which an identified entity was extracted.

10. The central data processor of claim 1, wherein the at least one data processing module further comprises a question/answer module configured to return a representation of relevant data in response to a question.

11. The central data processor of claim 1, wherein the at least one data processing module further comprises a summarization module configured to summarize a subset of the data.

12. The central data processor of claim 1, further comprising a formatting module in communication with the entity extraction module and the network extraction module configured to format the extracted entities and the extracted relationships into a visualization format.

13. The central data processor of claim 12, further comprising a communication module for communicating the visualization format generated by the formatting module to a host computer for rendering.

14. The central data processor of claim 13, wherein the visualization format is an entity network map where a plurality of the extracted entities are shown linked to each other via one or more of the extracted relationships.

15. The central data processor of claim 1, wherein the one or more influence relationships each comprise a direction and a magnitude of influence exerted by a first factor onto a second factor.

16. The central data processor of claim 15, wherein the magnitude and direction of the influence relationship is determined by a user on the host computer.

17. The central data processor of claim 15, wherein the magnitude and direction of the influence relationship is determined by the central data processor using the extracted relationships.

18. The central data processor of claim 15, wherein at least one factor has an influence relationship magnitude and direction for at least one other factor connected via an extracted relationship.

19. The central data processor of claim 15, wherein at least one extracted entity is graphically located on an influencer/influenced map according to a calculated value of the magnitudes and directions of every influence relationship associated with the extracted factor.

20. The central data processor of claim 1, wherein at least one user on a corresponding at least one host computer is able to interact with the modules in the central data processor via a graphical user interface installed on the at least one host computer.

21. The central data processor of claim 20, wherein the at least one data processing module further comprises a watch list module configured to allow a plurality of users on multiple host computers to share a list of terms, the list of terms being usable as an input to one or more of the modules.

22. The central data processor of claim 21, wherein the list of terms are selected from the extracted entities.

23. The central data processor of claim 21, wherein the searching module, in response to a macro, periodically searches the user-specified data sources and at least one of the data processing modules, in response to the macro, processes a data source found to include the list of terms input to the watch list module.

24. The central data processor of claim 2, wherein at least one option associated with at least one factor is assigned a value indicating a state of the at least one factor.

25. The central data processor of claim 24, wherein at least one option is associated with a risk model and the value associated with the option causes a change in the assigned values of a higher-level node in the risk model.

26. The central data processor of claim 24, wherein a macro performs one or more analytic steps and changes the value associated with a risk node, in response to the performing o the macro.

27. A central data processor, comprising:

access means for accessing data located on one or more networks;

communication means for communicating with a plurality of host computers;

at least one memory means for storing the data;

data processing means configured to process the relevant data, the data processing means comprising at least one of;

entity extraction means configured to extract entities from the relevant data; and

network extraction means configured to extract relationships between a subset of the extracted entities from the relevant data; and

scenario-building means for creating a system map comprising a plurality of factors, the plurality of factors being derived from the extracted entities and relationships and being related by at least one extracted relationship.

28. The central data processor of claim 27, further comprising searching means for searching the data in response to a search request received from at least one of the plurality of host computers, the searching means configured to return a representation of relevant data responsive to the search request.

29. The central data processor of claim 27, wherein the factors are selected from the extracted entities and organized according to the extracted relationships.

30. The central data processor of claim 27, further comprising formatting means for formatting the extracted entities and the extracted relationships into a visualization format that allows the at least one of the plurality of host computers to render a visualization of the extracted entities and relationships.

31. The central data processor of claim 27, wherein the data processing, means further comprises timeline extraction means configured to extract time information from the relevant data and to identify a time-based relationship between a plurality of the extracted entities.

32. The central data processor of claim 27, wherein the data processing means further comprises temporal analysis means configured to extract time information from the relevant data.

33. The central data processor of claim 27, wherein the data processing means further comprises cross-reference means in communication with the entity extraction means configured to extract entities from a subset of the data from which an identified entity was extracted.

34. The central data processor of claim 27, wherein the data processing means further comprises question/answer means configured to return a representation of relevant data in response to a question.

35. The central data processor of claim 27, wherein the data processing means further comprises summarization means configured to summarize a subset of the data.

36. The central data processor of claim 30, wherein the visualization format is an entity network map wherein at least one of the extracted entities are shown linked to another extracted entity via the extracted relationships.

37. The central data processor of claim 36, wherein at least one of the extracted relationships are represented by an influence relationship, the influence relationship having a direction and a magnitude of influence exerted by a first factor onto a second factor.

38. The central data processor of claim 37, wherein the magnitude and direction of the influence relationship is determined by a user on one of the plurality of host computers.

39. The central data processor of claim 37, wherein the magnitude and direction of the influence relationship is determined by the central data processor using the extracted relationships.

40. The central data processor of claim 37, wherein at least one factor has an influence relationship magnitude and direction for every other factor connected via an extracted relationship.

41. The central data processor of claim 37, wherein a plurality of factors are graphically located on an influencer/influenced map according to a summed value of the magnitudes and directions of every influence relationship associated with each respective factor.

42. The central data processor of claim 27, wherein the data processing means further comprises watch list means configured to allow users on the plurality of host computers to share a list of terms, wherein the list of terms is usable as an input for one or more of the data processing means.

43. The central data processor of claim 42, wherein the list of terms are selected from the extracted entities.

44. The central data processor of claim 42, wherein the searching means, in response to a macro, periodically searches the user-specified data sources and at least one of the data processing means, in response to the macro, processes a data source found to include the list of terms input to the watch list means.

45. The central data processor of claim 29, wherein each factor comprises at least one option associated with a risk model.

46. The central data processor of claim 45, wherein a change in a value associated with the option causes a change in an assigned value of an option for a higher-level node in the risk model.

47. The central data processor of claim 46, wherein a macro performs one or more analytic steps and changes the value associated with the option in response to the performing.

48. A computer readable medium containing instructions for performing a method for analyzing data, the method comprising:

searching a collection of data to find data relevant to a system;

processing the relevant data to extract entities and relationships between the entities;

inputting a plurality of factors that affect an outcome of the system, the factors being derived from the extracted entities and relationships;

creating a risk model comprising a hierarchy of nodes, wherein at least one of the nodes is representative of one of the factors, the represented factor comprising a value, and wherein the value of at least one other node in the risk model is being calculated using the value of the representative factor as an input; and

updating the value of the representative factor in response to the processing.

49. The computer readable medium of claim 48, the method further comprising setting influence values for a plurality of factors to indicate the amount of influence each of the plurality of factors has on another factor to which an extracted relationship exists.

50. The computer readable medium of claim 48, the method further comprising graphically viewing the factors and extracted relationships.

51. The computer readable medium of claim 49, the method further comprising updating the influence values and risk model after repeating the searching, processing, inputting and creating using a revised collection of data.

52. The computer readable medium of claim 49, the method further comprising updating the influence values and scenario dependency chart using a macro of operations after repeating the searching, processing, inputting and creating using a revised collection of data.

53. The computer readable medium of claim 52, wherein the macro is manually created by a user.

54. The computer readable medium of claim 52, wherein the macro is created by recording a user'"'"'s operations.

55. The computer readable medium of claim 50, wherein the inputting a plurality of factors is based on a user'"'"'s analysis of the graphically viewed factors and extracted relationships.

56. The computer readable medium of claim 49, wherein the influence values are set manually by a user.

57. The computer readable medium of claim 49, wherein the influence values are set automatically based on the extracted relationships.

58. The computer readable medium of claim 48, wherein the processing the relevant data includes extracting time information.

59. The computer readable medium of claim 50, wherein the graphically viewing includes rendering an entity network map where at least one of the factors are shown linked to at least one other factor via an extracted relationship.

60. The computer readable medium of claim 59, wherein the extracted relationship is represented by an influence relationship comprising an influence value exerted by a first factor onto a second factor.

61. The computer readable medium of claim 60, wherein a magnitude and direction of the influence relationship Is determined by a user.

62. The computer readable medium of claim 60, wherein a magnitude and direction of the influence relationship is determined automatically using the extracted relationships.

63. The computer readable medium of claim 60, wherein the graphically viewing further comprises graphically locating a plurality of the extracted entities on an influencer/influenced map according to a summed value of the influence values associated with each of the respective plurality of entities.