System, Method, and Computer Program for a Consumer Defined Information Architecture

• US 20100049766A1
• Filed: 08/31/2007
• Published: 02/25/2010
• Est. Priority Date: 08/31/2006
• Status: Active Grant

• Current Assignee: Primal Fusion Inc.
• Original Assignee: Primal Fusion Inc.
• Inventors: Sweeney, Peter, Good, Robert
• Granted Patent: US 8,510,302 B2
• Time in Patent Office: Days
• US Class Current: 707/737
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: G06F 16/353 into predefined classes
• CPC Class Codes: G06F 16/367 Ontology
• CPC Class Codes: G06F 16/84 Mapping; Conversion
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation

Abstract

A system, computer program, and method for organizing and managing data structures including based on input from a feedback agent is provided, the method including: (a) a method for faceted classification that is applicable to a domain of information, said method of faceted classification including: (i) a facet analysis of said domain or receiving the results of facet analysis of the domain; and (ii) applying a faceted classification synthesis of said domain; and (b) a complex-adaptive method for selecting and returning information, on one or more iterations, from said faceted classification synthesis, said complex-adaptive method varying the organizing and managing of data structures in response to said returned information. A system and method for faceted classification of a domain of information is also provided that includes providing a faceted data set including facet attributes with which to classify information, such facet attributes including optionally facet attribute hierarchies for the facet attributes; (b) providing a dimensional concept taxonomy in which the facet attributes are assigned to objects of the domain to be classified in accordance with concepts that associate meaning to the objects, said concepts being represented by concept definitions defined using said facet attributes and associated with the objects in the dimensional concept taxonomy, said dimensional concept taxonomy expressing dimensional concept relationships between the concept definitions in accordance with the faceted data set; and (c) providing or enabling a complex-adaptive system for selecting and returning dimensional concept taxonomy information to vary the faceted data set and dimensional concept taxonomy in response to the dimensional concept taxonomy information. In another aspect of the method of the present invention the method for faceted classification of the domain of information further includes performing faceted classification synthesis to relate a set of concepts represented by concept definitions defined in accordance with a faceted data set including facet attributes, and optionally facet attribute hierarchies. The invention also provides a computer system for enabling a user to manipulate dimensional concept relationships. A further aspect of the system is a system for organizing and managing data structures including based on input from a feedback agent, in which the system includes or is linked to a complex-adaptive system for selecting and returning dimensional concept taxonomy information to vary a faceted data set and a dimensional concept taxonomy in response to dimensional concept taxonomy information, the dimensional concept taxonomy expressing dimensional concept relationships between the concept definitions in accordance with the faceted data set.

Claims

1. A method for organizing and managing data structures including based on input from a feedback agent characterized by:

a) a method for faceted classification that is applicable to a domain of information, said method of faceted classification including;

(i) a facet analysis of said domain or receiving the results of facet analysis of the domain; and

(ii) applying a faceted classification synthesis of said domain; and

b) a complex-adaptive method for selecting and returning information, on one or more iterations, from said faceted classification synthesis, said complex-adaptive method varying the organizing and managing of data structures in response to said returned information.

2. A method for faceted classification of a domain of information characterized by:

a) providing a faceted data set including facet attributes with which to classify information, such facet attributes including optionally facet attribute hierarchies for the facet attributes;

b) providing a dimensional concept taxonomy in which the facet attributes are assigned to objects of the domain to be classified in accordance with concepts that associate meaning to the objects, said concepts being represented by concept definitions defined using said facet attributes and associated with the objects in the dimensional concept taxonomy, said dimensional concept taxonomy expressing dimensional concept relationships between the concept definitions in accordance with the faceted data set; and

c) providing or enabling a complex-adaptive system for selecting and returning dimensional concept taxonomy information to vary the faceted data set and dimensional concept taxonomy in response to the dimensional concept taxonomy information.

3. The method of claim 2 wherein the facet analysis of input information is selected from a domain of information in accordance with a source data structure, the method being characterized by

discovering at least one of the facet attributes of the input information using pattern augmentation and/or statistical analyses to identify patterns of facet attribute relationships in the input information.

4. The method of claim 3 characterized by:

inferring the facet attribute relationships from concept definitions and concept relationships obtained from the input information thereby enabling the building of facet attribute hierarchies, said concept definitions including attributes for defining said facet attributes.

5. The method of claim 4 characterized by:

establishing potential facet attribute relationships from permutations of facet attribute relationships in concept definitions and concept relationships in the input information.

6. The method of claim 5 characterized by:

establishing facet attribute relationships from potential facet attribute relationships to reduce the number of potential facet attribute relationships in order to augment the patterns for statistical analyses.

7. The method of claim 6 characterized by:

establishing potential facet attribute relationships in accordance with at least one of;

(a) the presence of facet attributes shared across a pair of related concept definitions;

(b) the presence of the facet attribute relationship, directly or indirectly, in the facet attribute hierarchy; and

(c) an external lexicon.

8. The method of claim 7 characterized by:

for each potential facet attribute relationship, evaluating the likelihood that a respective potential facet attribute relationship remains applicable substantially throughout the concept relationships in which the respective potential facet attribute relationship presents; and

making the respective potential facet attribute relationship a candidate facet attribute relationship for the facet attribute hierarchy in response to said evaluating.

9. The method of claim 8 characterized by:

said evaluating including determining a prevalence of the respective potential facet attribute relationship in the aggregate context of all concept relationships and wherein said making is responsive to said prevalence.

10. The method of claim 8 characterized by:

said evaluating including identifying the presence of circular relationships among the potential facet attribute relationships and identifying respective potential facet attribute relationships that contradict an assumption of hierarchy therebetween, and wherein said making is responsive to said identifying.

11. The method of claim 8 characterized by:

assembling the candidate facet attribute relationships into a facet attribute polyhierarchy such that the set of candidate facet attribute relationships in the polyhierarchy is substantially logically consistent in the aggregate.

12. The method of claim 4 characterized by:

defining the facet attribute hierarchies as a strict hierarchy by reconsidering the order of a facet attribute having multiple parents as an attribute of an ancestor of the multiple parents.

13. The method of claim 12 characterized by:

determining the facets from root nodes within the facet attribute hierarchy.

14. The method of claim 3 characterized by:

the facet attributes being morphemes and the facet attribute relationships being morpheme relationships.

15. The method of claim 14 characterized by:

using the facet attributes and optionally the facet attribute hierarchy to perform facet analysis on further input information selected from a second domain of information.

16. The method of claim 3 characterized by:

providing a faceted data set including the facet attributes and optionally the facet attribute hierarchy.

17. The method of claim 16 characterized by:

using the faceted data set for facet classification synthesis.

18. The method of claim 2 characterized by:

accessing a data store that includes a plurality of statistical analyses, and by operation of the complex-adaptive system using said statistical analyses for varying the faceted data set and dimensional concept taxonomy by aggregating selected dimensional concept taxonomy information.

27. The method of claim 2 characterized by:

performing faceted classification synthesis to relate a set of concepts represented by concept definitions defined in accordance with a faceted data set including facet attributes, and optionally facet attribute hierarchies, said faceted classification synthesis including;

expressing dimensional concept relationships between the concept definitions, wherein two concept definitions are determined to be related in a particular dimensional concept relationship by examining whether at least one of explicit relationships and implicit relationships exist in the faceted data set between the respective facet attributes of the two concept definitions.

28. The method of claim 27 characterized by:

assembling the dimensional concept relationships in a dimensional concept hierarchy.

29. The method of claim 27 characterized by:

defining a dimensional axis, from one or more facet attributes, with which to generate a dimensional concept hierarchy from the dimensional concept relationships.

30. The method of claim 29 characterized by:

defining one or more of;

(i) a domain to be classified; and

(ii) an active concept, from among the set of concepts, which serves as either an ancestor concept or a descendent concept from which the dimensional concept hierarchy is generated.

31. The method of claim 27 characterized by:

the respective facet attributes of the two concept definitions define either an ancestor or descendent relationship therebetween.

32. The method of claim 30 characterized by:

defining the active concept from one or more concepts in the domain.

33. The method of claim 30 characterized by:

if the active concept is defined, defining the dimensional axis from one or more facet attributes of the active concept.

34. The method of claim 30 characterized by:

defining one or more of the domain, the active concept, and the dimensional axis by means of human input.

35. The method of claim 30 characterized by:

defining one or more of the domain, the active concept, and the dimensional axis by means of machine input.

36. The method of claim 29 characterized by:

defining a limit for the number of hierarchical steps in the dimensional concept hierarchy.

37. The method of claim 29 characterized by:

defining a limit for the number of concepts to relate.

38. The method of claims 36 or 37 characterized by:

defining the limit by means of a human input.

39. The method of claims 36 or 37 characterized by:

defining the limit by means of a machine input.

40. The method of claim 27 characterized by:

defining a plurality of dimensional axes, each axis defined in accordance with respective sets of one or more facet attributes, so as to define a plurality of dimensional concept hierarchies.

41. The method of claim 29 characterized by:

associating two concept definitions in a particular dimensional concept relationship, on a particular dimensional axis, if the facet attributes of one of the two concept definitions are related to all or a subset of facet attributes of another of the two concept definitions.

42. The method of claim 29 characterized by:

associating two concept definitions in a particular dimensional concept relationship, on a particular dimensional axis, if a subset of the facet attributes of one of the two concept definitions are associated to all or a subset of facet attributes of another of the two concept definitions.

43. The method of claim 29 characterized by:

selecting one or more facet attributes for defining said dimensional axis, said selecting in accordance with at least one of;

(i) the respective priorities of the facet attributes in the facet attribute hierarchy;

(ii) and a particular concept definition including the one or more facet attributes to associate a particular meaning to said dimensional axis.

44. The method of claim 27 characterized by:

evaluating sets of dimensional concept relationships for the presence of indirect relationships and assembling the dimensional concept hierarchy without the indirect relationships.

45. The method of claim 27 characterized by:

establishing a priority for the concept definitions in the dimensional concept hierarchy based on at least one of;

(i) priorities of facet attributes in the facet attribute hierarchy, and (ii) an analysis of the facet attributes in the respective concept definitions of related concepts.

46. The method of claim 27 characterized by:

defining a dimensional concept taxonomy by assigning facet attributes to content nodes of a domain to be classified in accordance with concepts associated with the content nodes, said concepts being represented by concept definitions in the dimensional concept hierarchy defined using said facet attributes.

47. The method of claim 27 characterized by:

inferring a concept relationship between two or more concept definitions where there is no explicit concept relationship between the two concept definitions.

48. The method of claim 46 characterized by:

inferring a concept as a concept definition defined by one or more facet attributes where there is no associated content node in the domain associated with the other of the two concept definitions.

49. The method of claim 27 characterized by:

defining said dimensional concept relationships for a domain to be classified, said domain including one or more content nodes each associated with one or more concepts represented by the concept definitions.

50. The method of claim 49 characterized by:

examining concept nodes for their respective one or more concept definitions.

51. The method of claim 49 characterized by:

defining said dimensional concept relationships for a domain to be classified such that said defining is limited to processing a localized region of the domain using content nodes proximal to a selected content node.

52. The method of claim 2 characterized by:

relating said concepts by defining a set of candidate concept definitions that are determined to be proximal to one another by analyzing the facet attributes or a subset thereof associated with said concepts.

53. The method of claim 27 characterized by:

deriving a set of candidate concept definitions associated with the two concepts by establishing concept definitions that are proximal to one another by defining the facet attribute hierarchy based on facet attributes associated with the two concepts.

87. The method of claim 49 characterized by:

defining said dimensional concept relationships for a domain to be classified such that said defining is limited to real-time processing using concept definitions proximal to a selected concept definition.

88. The method of claim 49 characterized by:

defining said dimensional concept relationships for a domain to be classified such that said defining is limited in time for latency control.

19. A system for organizing and managing data structures including based on input from a feedback agent characterized in that:

the system includes or is linked to a complex-adaptive system for selecting and returning dimensional concept taxonomy information to vary a faceted data set and a dimensional concept taxonomy in response to dimensional concept taxonomy information, wherein;

the system is operable to process a faceted data set including facets, facet attributes, and, optionally, facet attribute hierarchies for the facet attributes with which to classify information; and

the system is further operable to define the dimensional concept taxonomy in which the facet attributes are assigned to objects of the domain to be classified in accordance with concepts that associate meaning to the objects, said concepts being represented by concept definitions defined using said facet attributes and associated with the objects in the dimensional concept taxonomy, said dimensional concept taxonomy expressing dimensional concept relationships between the concept definitions in accordance with the faceted data set.

20. The system of claim 19 characterized in that:

the complex-adaptive system is operable to (i) process input information selected from a domain of information in accordance with a source data structure, and (ii) discover at least one of the facet attributes, or optionally one of the facet attribute hierarchies, of the input information using pattern augmentation and/or statistical analyses to identify patterns of facet attribute relationships in the input information.

21. The system of claim 19 characterized in that:

the complex-adaptive system is operable to return further input information for reinforcing the facet attributes, or optionally the facet attribute hierarchies, which constitute the basis for the returned further input information, said further input information being derived from one or more of machine-based or user-based return paths.

22. The system of claim 21 characterized in that

(a) the further input information is obtained by means of a request for further input information generated by the complex-adaptive system, and

(b) such request is associated with a time limit for responding to such request.

23. The system of claim 19 characterized in that:

the complex-adaptive system includes or is linked to a data store of statistical analyses; and

the complex-adaptive system is operable to vary the faceted data set and dimensional concept taxonomy based on the statistical analyses by aggregating selected dimensional concept taxonomy information.

24. The system of claim 22 characterized in that:

the complex-adaptive system is operable to control the varying of the faceted data set and dimensional concept taxonomy in response to the dimensional concept taxonomy information.

25. The system of claim 23 characterized in that:

the complex-adaptive system is operable to apply one or more of (i) statistical hurdles and (ii) pattern-matching constraints, to the facets, the facet attributes, and the facet attribute hierarchies, for the facet attributes derived from the dimensional concept taxonomy information.

26. The system of claim 19 characterized in that:

the complex-adaptive system includes a machine-based complex adaptive system that is operable to use statistical analyses to analyze the dimensional concept taxonomy and select a dimensional concept taxonomy information to return.

54. A computer system for performing facet analysis of input information selected from a domain of information in accordance with a source data structure, characterized in that:

the computer system is operable to derive facet attributes, and optionally facet attribute hierarchies, of the input information using pattern augmentation and statistical analyses to identify patterns of facet attribute relationships in the input information.

55. The computer system of claim 54 characterized in that:

the computer system is operable to infer the facet attribute relationships from concept definitions and concept relationships obtained from the input information thereby to build the facet attribute hierarchies, said concept definitions including attributes for defining said facet attributes.

56. The computer system of claim 55 characterized in that:

the computer system if operable to build the facet attribute hierarchy by adding facet attribute relationships incrementally.

57. The computer system of claim 55 characterized in that:

the computer system is operable to derive potential facet attribute relationships from permutations of facet attribute relationships in concept definitions and concept relationships in the input information.

58. The computer system of claim 57 characterized in that:

the computer system is operable to order the processing of the potential facet attribute relationships in accordance with a count of facet attributes in the concept definitions of a concept relationship pair.

59. The computer system of claim 57 characterized in that:

the computer system is operable to align facet attribute relationships from the potential facet attribute relationships to reduce the number of potential facet attribute relationships to augment the patterns for statistical analyses.

60. The computer system of claim 57 characterized in that:

the computer system is operable to align the potential facet attribute relationships in accordance with at least one of;

(a) the presence of facet attributes shared across a pair of related concept definitions;

(b) the presence of the facet attribute relationship, directly or indirectly, in the facet attribute hierarchy; and

(c) an external lexicon.

61. The computer system of claim 57 characterized in that:

the computer system is operable, for each potential facet attribute relationship, to evaluate the likelihood that a respective potential facet attribute relationship remains applicable substantially throughout the concept relationships in which the respective potential facet attribute relationship presents; and

making the respective potential facet attribute relationship a candidate facet attribute relationship for the facet attribute hierarchy in response to the evaluating.

62. The computer system of claim 61 characterized in that:

said evaluating includes determining a prevalence of the respective potential facet attribute relationship in the aggregate context of all concept relationships and wherein said making is responsive to said prevalence.

63. The computer system of claim 62 characterized in that:

said evaluating includes determining the presence of circular relationships among the potential facet attribute relationships and identifying respective potential facet attribute relationships that contradict an assumption of hierarchy therebetween and wherein said making is responsive to said identifying.

64. The computer system of claim 62 characterized in that:

the computer system is operable to prune one of the candidate facet attribute relationships if said one can be logically constructed using sets of other candidate facet attribute relationships.

65. The computer system of claim 62 characterized in that:

the computer system is operable to assemble the candidate facet attribute relationships into a facet attribute polyhierarchy such that the set of candidate facet attribute relationships in the polyhierarchy is substantially logically consistent in the aggregate.

66. The computer system of claim 65 characterized in that:

the computer system is operable such that said assembling uses the least number of polyhierarchical relationships necessary to create the logically consistent polyhierarchy.

67. The computer system of claim 65 characterized in that:

the computer system is operable such that said assembling orders a respective facet attribute in the polyhierarchy in response to a measure of a relative generality of each facet attribute.

68. The computer system of claim 67 characterized in that:

the computer system is operable such that a respective facet attribute'"'"'s generality is determined using a generality of one or more concept definitions associated with the respective facet attribute.

69. The computer system of claim 54 characterized in that:

the computer system is operable to define the facet attribute hierarchy as a strict hierarchy by reconsidering the order of a facet attribute having multiple parents as an attribute of an ancestor of the multiple parents.

70. The computer system of claim 54 characterized in that:

the computer system is operable to determine the facet attributes from root nodes within the facet attribute hierarchy.

71. The computer system of claim 54 characterized in that:

the computer system is operable to derive from the input information the concept definitions and the concept relationships, wherein the concept definitions are defined as facet attributes.

72. The computer system of claim 54 characterized in that:

the computer system is operable to identify structural markers in the input information and extract attributes from the input information responsive to said structural markers.

73. The computer system of claim 54 characterized in that:

the facet attributes are morphemes, and the facet attribute relationships are morpheme relationships.

74. The computer system of claim 54 characterized in that:

the computer system is operable using the facet attributes to perform facet analysis on further input information selected from a second domain of information.

75. The computer system of claim 54 characterized in that:

the computer system is operable to provide a faceted data set including the facet attributes and optionally the facet attribute hierarchy.

76. The computer system of claim 75 characterized in that:

The computer system is operable to provide the faceted data set for sharing among a plurality of domains with which to derive respective dimensional concept taxonomies for each domain.

77. The computer system of claim 75 characterized in that:

the computer system is operable to use the faceted data set for facet classification synthesis.

78. A computer system for enabling a user to manipulate dimensional concept relationships, characterized in that the computer system comprises:

a processor;

a computer-readable medium in data communication with the processor, where the computer-readable medium includes thereon processor executable instructions and a plurality of data elements determined to be related in a particular dimensional concept relationship;

an input utility configured to allow an outside entity to interface with the processor;

a display operative to provide a visual depiction of at least selected data elements; and

an editor allowing the outside entity to modify the data elements and the particular dimensional concept relationship.

79. The computer system of claim 78 characterized in that:

the editor comprises a web page that renders a view of at least a portion of the data elements corresponding to an active node selected by the outside entity.

80. The computer system of claim 79 characterized in the active node is presented in a tree fragment form.

81. The computer system of claim 78 characterized in that the data elements include concept definitions and the editor allows the outside entity to modify concept definitions.

82. The computer system of claim 78 characterized in that the data elements include hierarchical data and the editor allows the outside entity to modify hierarchical data.

83. The computer system of claim 78 characterized in that the data elements include content nodes and the editor allows the outside entity to change the position of a content node associated with concepts relative to other content nodes associated with concepts in the dimensional concept taxonomy.

84. The computer system of claim 78 characterized in that the editor allows the outside entity to change definitions describing the subject matter of a content node.

85. The computer system of claim 78 characterized in that the editor further allows display of data element modifications to an outside entity.

86. The computer system of claim 78 characterized in that the editor further allows storage of data element modifications on the computer-readable medium.