System and method for harmonizing content relevancy across structured and unstructured data

• US 20050086215A1
• Filed: 10/22/2004
• Published: 04/21/2005
• Est. Priority Date: 06/14/2002
• Status: Abandoned Application

• Current Assignee: Entopia, Inc.
• Original Assignee: Entopia, Inc.
• Inventors: Perisic, Igor
• Application Number:
  US10/972,248
• Publication Number:
  US 20050086215A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9538 Presentation of query results
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access

Abstract

A search request is received from a requester including one or more search terms. In response to the search request, one or more objects are located that fulfill the search request. A relevancy score is computed for the one or more objects based on whether the object(s) include structured or unstructured data. The relevancy scores enable the requestor to determine the content relevancy of one or more objects.

Claims

1. A method for retrieving information, comprising:

receiving a search request from a requester including one or more search terms;

searching a plurality of objects based on at least one search term;

identifying at least one object associated with at least one search term; and

determining a relevancy score for the object based on whether the object includes structured or unstructured data.

2. The method of claim 1, wherein the plurality of objects includes some objects containing structured data and the relevancy score is determined at least in part on whether the structured data includes restricted or unrestricted fields.

3. The method of claim 2, wherein restricted fields are associated with a first set of modifier values and unrestricted fields are associated with a second set of modifier values.

4. The method of claim 3, wherein at least some of the modifiers are adjustable.

5. The method of claim 1, further comprising:

adjusting the relevancy score based on contributor expertise.

6. The method claim 1, further comprising:

adjusting the relevancy score based on creator expertise.

7. The method claim 1, further comprising:

adjusting the relevancy score based on requestor expertise.

8. The method of claim 1, wherein the relevancy score is determined from a function that is based on one or more operators used in the search request.

9. The method of claim 8, wherein the one or more operators include at least one Boolean operator.

10. The method of claim 8, wherein the one or more operators include at least one proximity operator.

11. The method of claim 8, wherein the one or more operators include a combination of Boolean and proximity operators.

12. The method of claim 8, wherein the step of determining a relevancy score, comprises:

identifying objects that include structured data;

searching for a first keyword match in the structured data;

determining a first set of intrinsic scores for the first keyword based at least in part on the number of matches in the structured data;

searching for a second keyword match in the structured data, when a second keyword is present in the search request;

determining a second set of intrinsic scores for the second keyword, when present in the search request, based at least in part on the number of matches in the structured data;

searching for subsequent keywords matches in the structured data, when subsequent keywords are present in the search request;

determining subsequent sets of intrinsic scores for subsequent keywords, when present in the search query, based at least in part on the number of matches in the structured data;

modifying the first, second and subsequent sets of intrinsic scores with modifier values to produce first, second and subsequent sets of modified intrinsic scores, wherein the modifier values are based at least in part on whether the structured data is restricted or unrestricted;

determining an adjusted intrinsic score across one or more fields within the structured data from the first set of modified intrinsic scores associated with the first keyword;

determining an adjusted intrinsic score across one or more fields within the structured data from the second set of modified intrinsic scores associated with the second keyword;

determining adjusted intrinsic scores across one or more fields within the structured data from the subsequent sets of modified intrinsic scores associated with the subsequent keywords; and

selecting the relevancy score to be determined by a function aggregating the adjusted intrinsic scores of the first, second and subsequent keywords.

13. The method of claim 12, wherein the adjusted intrinsic score is dependent on one or more operators within the search query.

14. The method of claim 13, wherein the one or more operators include at least one Boolean operator.

15. The method of claim 13, wherein the one or more operators include at least one proximity operator.

16. The method of claim 13, wherein the one or more operators include a combination of Boolean and proximity operators.

17. The method of claim 12, wherein the adjusted intrinsic scores of the first, second and subsequent keywords are normalized.

18. The method of claim 12, wherein the adjusted intrinsic scores of the first, second and subsequent keywords are weighted by a convex function.

19. The method of claim 12, wherein the adjusted intrinsic scores of the first, second and subsequent keywords are weighted by a concave function.

20. The method of claim 12, wherein the adjusted intrinsic scores of the first, second and subsequent keywords are weighted by a partly concave and a partly convex function.

21. The method of claim 20, wherein the partly concave and partly convex function is an inverse logit function.

22. The method of claim 12, wherein the aggregation function is either a Maximum or a Minimum over the adjusted intrinsic scores.

23. The method of claim 12, wherein the aggregation function is based on a sum or average over the adjusted intrinsic scores.

24. The method of claim 12, wherein the aggregation function is one of a group of aggregation functions including a convex function, a concave function or a partly convex and partly concave function over the adjusted intrinsic scores.

25. The method of claim 24, wherein the aggregation function is an inverse logit function.

26. A computer-readable medium having instructions stored thereon, which, when executed by a processor, causes the processor to perform the operations of:

receiving a search request from a requester including one or more search terms;

searching a plurality of objects based on at least one search term;

identifying at least one object associated with at least one search term; and

determining a relevancy score for the object based on whether the object includes structured or unstructured data.

27. The computer-readable medium of claim 26, wherein the plurality of objects includes some objects containing structured data and the relevancy score is determined at least in part on whether the structured data includes restricted or unrestricted fields.

28. The computer-readable medium of claim 27, wherein restricted fields are associated with a first set of modifier values and unrestricted fields are associated with a second set of modifier values.

29. The computer-readable medium of claim 26, wherein at least some of the modifiers are adjustable.

30. The computer-readable medium of claim 26, further comprising:

adjusting the relevancy score based on contributor expertise.

31. The computer-readable medium of claim 26, further comprising:

adjusting the relevancy score based on creator expertise.

32. The computer-readable medium claim 26, further comprising:

adjusting the relevancy score based on requestor expertise.

33. The computer-readable medium of claim 26, wherein the relevancy score is determined from a function that is based on one or more operators used in the search request.

34. The computer-readable medium of claim 33, wherein the one or more operators includes at least one Boolean operator.

35. The computer-readable medium of claim 33, wherein the one or more operators includes at least one proximity operator.

36. The computer-readable medium of claim 33, wherein the one or more operators includes a combination of Boolean and proximity operators.

37. The computer-readable medium of claim 33, wherein the step of determining a relevancy score, comprises:

identifying objects that include structured data;

searching for a first keyword match in the structured data;

determining a first set of intrinsic scores for the first keyword based at least in part on the number of matches in the structured data;

searching for a second keyword match in the structured data, when a second keyword is present in the search request;

determining a second set of intrinsic scores for the second keyword, when present in the search request, based at least in part on the number of matches in the structured data;

searching for subsequent keywords matches in the structured data, when subsequent keywords are present in the search request;

determining subsequent sets of intrinsic scores for subsequent keywords, when present in the search query, based at least in part on the number of matches in the structured data;

modifying the first, second and subsequent sets of intrinsic scores with modifier values to produce first, second and subsequent sets of modified intrinsic scores, wherein the modifier values are based at least in part on whether the structured data is restricted or unrestricted;

determining an adjusted intrinsic score across one or more fields within the structured data from the first set of modified intrinsic scores associated with the first keyword;

determining an adjusted intrinsic score across one or more fields within the structured data from the second set of modified intrinsic scores associated with the second keyword;

determining adjusted intrinsic scores across one or more fields within the structured data from the subsequent sets of modified intrinsic scores associated with the subsequent keywords; and

selecting the relevancy score to be determined by a function aggregating the adjusted intrinsic scores of the first, second and subsequent keywords.

38. The computer-readable medium of claim 37, wherein the adjusted intrinsic score is dependent on one or more operators within the search query.

39. The computer-readable medium of claim 37, wherein the one or more operators include at least one Boolean operator.

40. The computer-readable medium of claim 37, wherein the one or more operators include at least one proximity operator.

41. The computer-readable medium of claim 37, wherein the one or more operators include a combination of Boolean and proximity operators.

42. The computer-readable medium of claim 37, wherein the adjusted intrinsic scores of the first, second and subsequent keywords are normalized.

43. The computer-readable medium of claim 37, wherein the adjusted intrinsic scores of the first, second and subsequent keywords are weighted by a convex function.

44. The computer-readable medium of claim 37, wherein the adjusted intrinsic scores of the first, second and subsequent keywords are weighted by a concave function.

45. The computer-readable medium of claim 37, wherein the adjusted intrinsic scores of the first, second and subsequent keywords are weighted by a partly concave and a partly convex function.

46. The computer-readable medium of claim 45, wherein the partly concave and partly convex function is an inverse logit function.

47. The computer-readable medium of claim 37, wherein the aggregation function is either a Maximum or a Minimum over the adjusted intrinsic scores.

48. The computer-readable medium of claim 37, wherein the aggregation function is based on a sum or average over the adjusted intrinsic scores.

49. The computer-readable medium of claim 37, wherein the aggregation function is one of a group of aggregation functions including a convex function, a concave function or a partly convex and partly concave function over the adjusted intrinsic scores.

50. The computer-readable medium of claim 49, wherein the aggregation function is an inverse logit function.

51. An information retrieval system, comprising:

a processor;

a memory coupled to the processor and including instructions, which, when executed by the processor, causes the processor to perform the operations of;

receiving a search request from a requester including one or more search terms;

searching a plurality of objects based on at least one search term;

identifying at least one object associated with at least one search term; and

determining a relevancy score for the object based on whether the object includes structured or unstructured data.

52. The system of claim 51, wherein the plurality of objects includes some objects containing structured data and the relevancy score is determined at least in part on whether the structured data includes restricted or unrestricted fields.

53. The system of claim 52, wherein restricted fields are associated with a first set of modifier value and unrestricted fields are associated with a second set of modifier value.

54. The system of claim 51, wherein at least some of the modifiers are adjustable.

55. The system of claim 51, further comprising:

adjusting the relevancy score based on contributor expertise.

56. The system of claim 51, further comprising:

adjusting the relevancy score based on creator expertise.

57. The system of claim 51, further comprising:

adjusting the relevancy score based on requestor expertise.

58. The system of claim 51, wherein the relevancy score is determined from a function that is based on one or more operators used in the search request.

59. The system of claim 58, wherein the one or more operators include at least one Boolean operator.

60. The system of claim 58, wherein the one or more operators include at least one proximity operator.

61. The system of claim 58, wherein the one or more operators include a combination of Boolean and proximity operators.

62. The system of claim 58, wherein the step of determining a relevancy score, comprises:

identifying objects that include structured data;

searching for a first keyword match in the structured data;

determining a first set of intrinsic scores for the first keyword based at least in part on the number of matches in the structured data;

searching for a second keyword match in the structured data, when a second keyword is present in the search request;

determining a second set of intrinsic scores for the second keyword, when present in the search request, based at least in part on the number of matches in the structured data;

searching for subsequent keywords matches in the structured data, when subsequent keywords are present in the search request;

determining subsequent sets of intrinsic scores for subsequent keywords, when present in the search query, based at least in part on the number of matches in the structured data;

modifying the first, second and subsequent sets of intrinsic scores with modifier values to produce first, second and subsequent sets of modified intrinsic scores, wherein the modifier values are based at least in part on whether the structured data is restricted or unrestricted;

determining an adjusted intrinsic score across one or more fields within the structured data from the first set of modified intrinsic scores associated with the first keyword;

determining an adjusted intrinsic score across one or more fields within the structured data from the second set of modified intrinsic scores associated with the second keyword;

determining adjusted intrinsic scores across one or more fields within the structured data from the subsequent sets of modified intrinsic scores associated with the subsequent keywords; and

selecting the relevancy score to be determined by a function aggregating the adjusted intrinsic scores of the first, second and subsequent keywords.

63. The system of claim 62, wherein the adjusted intrinsic score is dependent on one or more operators within the search query.

64. The system of claim 62, wherein the one or more operators include at least one Boolean operator.

65. The system of claim 62, wherein the one or more operators include at least one proximity operator.

66. The system of claim 62, wherein the one or more operators include a combination of Boolean and position operators.

67. The system of claim 62, wherein the adjusted intrinsic scores of the first, second and subsequent keywords are normalized.

68. The system of claim 62, wherein the adjusted intrinsic scores of the first, second and subsequent keywords are weighted by a convex function.

69. The system of claim 62, wherein the adjusted intrinsic scores of the first, second and subsequent keywords are weighted by a concave function.

70. The system of claim 62, wherein the adjusted intrinsic scores of the first, second and subsequent keywords are weighted by a partly concave and a partly convex function.

71. The system of claim 70, wherein the partly concave and partly convex function is an inverse logit function.

72. The system of claim 62, wherein the aggregation function is either a Maximum or a Minimum over the adjusted intrinsic scores.

73. The system of claim 62, wherein the aggregation function is based on a sum or average over the adjusted intrinsic scores.

74. The system of claim 62, wherein the aggregation function is one of a group of aggregation functions including a convex function, a concave function or a partly convex and partly concave function over the adjusted intrinsic scores.

75. The system of claim 74, wherein the aggregation function is an inverse logit function.