Methods and apparatus for matching entities and for predicting an attribute of an entity based on an attribute frequency value

• US 6,018,738 A
• Filed: 01/22/1998
• Issued: 01/25/2000
• Est. Priority Date: 01/22/1998
• Status: Expired due to Term

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Kadie, Carl M., Breese, John S.
• Primary Examiner(s): Amsbury, Wayne
• Assistant Examiner(s): ALAM, SHAHID AL
• Application Number:
  US09/010,824
• Time in Patent Office: 733 Days
• Field of Search: 707/5, 707/3, 707/100, 707/102, 707/500, 707/501, 707/1, 707/6, 707/103, 707/104, 706/11, 345/327, 345/356
• US Class Current: 707/749
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: Y10S 707/962 Entity-attribute-value
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access

Abstract

Matching (e.g., via correlation or similarity process) entities having attributes, some of which have associated values. The values of the attributes may be adjusted based on number of entities that have values for a particular attribute so that the values decrease as the number increases. The attributes of the entities may be harmonized and provided with default values so that entities being matched have common attributes defined by the union of the attributes of the entities being matched. The attributes of the entities may be expanded and provided with default values so that the entities being matched have attributes that neither had originally. The match values may be normalized to provide a weight value which may be used to predict an attribute value of a new entity based on known attribute values of known entities. The weight values may be tuned such that relatively high weights are amplified and relatively low weights are suppressed.

Claims

1. A method for operating a machine to generate a determination of a degree to which (i) a new entity having at least one attribute with an associated attribute value, and (ii) one entity selected from a group of entities, each entity of the group of entities having at least one attribute with an associated attribute value, match, the method comprising steps of:

a) accepting, by the machine, information relating to the new entity, the entities of the group of entities, and the attributes and attribute values of the new entity and the entities of the group of entities;

b) for each of the at least one attribute of each entity of the group of entities, adjusting, with the machine, the attribute value associated therewith based on a frequency of the at least one attribute throughout the entities of the group of entities to thereby generate an adjusted attribute value; and

c) determining, with the machine, a degree to which (i) the new entity and (ii) the one entity match based on the attribute value associated with each of the at least one attribute of the new entity and the adjusted attribute value of each of the at least one attribute of the one entity.

2. The method of claim 1 wherein the step of adjusting the attribute value associated with each of the at least one attribute of each of the entities of the group of entities includes sub-steps of:

i) for each of the at least one attribute, over all entities of the group of entities, determining, with the machine, a number of times an attribute value exists for the at least one attribute to generate an attribute frequency value; and

ii) for each entity of the group of entities and for each of the at least one attribute, adjusting, with the machine, the attribute value of the at least one attribute such that the adjusted attribute value decreases as the attribute frequency value increases.

3. The method of claim 2 wherein the attribute value is divided by the attribute frequency value to form the adjusted attribute value.

4. The method of claim 2 wherein the adjusted attribute value is an inverse function of the attribute frequency value.

5. The method of claim 1 wherein the step of adjusting, for each of the at least one attribute of each entity of the group of entities, the attribute value associated therewith includes sub-steps of:

i) for each of the at least one attribute, over all entities of the group of entities, determining, with the machine, the number of times an attribute value of the at least one attribute belongs to a predetermined set of values to generate an attribute frequency value; and

ii) for each entity of the group of entities and for each of the at least one attribute, adjusting, with the machine, the attribute value of the at least one attribute such that the adjusted attribute value decreases as the attribute frequency value increases,

wherein the at least one attribute is a value attribute.

6. The method of claim 1 wherein the step of adjusting, for each of the at least one attribute of each entity of the group of entities, the attribute value associated therewith includes sub-steps of:

i) over each of the at least one attribute, over all entities of the group of entities, determining, with the machine, a running sum of an attribute value of the at least one attribute to generate an attribute frequency value; and

ii) for each entity of the group of entities and for each of the at least one attribute, adjusting, with the machine, the attribute value of the at least one attribute such that the adjusted attribute frequency value decreases as the attribute frequency value increases,

wherein the at least one attribute is a value attribute.

7. The method of claim 1 wherein the step of determining a degree to which (i) the new entity and (ii) the one entity match, includes a sub-step of:

i) for each of the at least one attribute, if the attribute value of the at least one attribute of the new entity matches the attribute value of the at least one attribute of the one entity, then adding, with the machine, the adjusted attribute value of the at least one attribute of the one entity to a running sum,

wherein the degree to which (i) the new entity and (ii) the one entity match is based on a final value of the running sum over each of the at least one attribute.

8. The method of claim 1 wherein the step of determining a degree to which the new entity and the one entity match includes a step of determining a similarity between the new entity and the one entity based on the attribute value associated with each of the at least one attribute of the new entity and the adjusted attribute value of each of the at least one attribute of the one entity.

9. The method of claim 8 wherein the step of determining a similarity between the new entity and the one entity includes sub-steps of:

i) for each of the at least one attribute of the new entity, determining, with the machine, a normalized attribute value associated with the at least one attribute value; and

ii) determining, with the machine, a similarity between the new entity and the one entity based on each of the at least one normalized attribute value associated with each of the at least one attribute of the new entity and the each of the at least one adjusted attribute value of each of the at least one attribute of the one entity.

10. The method of claim 9 wherein the step of, for each of the at least one attribute of the new entity, determining a normalized attribute value associated with the at least one attribute value includes sub-steps of:

i) for each of the at least one attribute of the new entity, determining, with the machine, an adjusted attribute value;

ii) determining, with the machine, a square root of a sum of squares of the at least one adjusted attribute value associated with the at least one attribute of the new entity; and

iii) for each of the at least one attribute of the new entity, dividing, with the machine, an associated adjusted attribute value by the square root.

11. The method of claim 8 wherein the step of adjusting, for each of the at least one attribute of each entity of the group of entities, the attribute value associated therewith includes sub-steps of:

i) for each of the at least one attribute, over all entities of the group of entities, determining, with the machine, a number of times an attribute value exists for the at least one attribute to generate an attribute frequency value; and

ii) adjusting, with the machine, each of the at least one attribute such that the adjusted attribute decreases as the attribute frequency value increases.

12. The method of claim 11 wherein the sub-step of adjusting each of the at least one attribute includes further steps of:

iii) determining, with the machine, a total number of entities of the group of entities;

iv) for each of the at least one attribute, dividing, with the machine, the total number of entities by the attribute frequency value to form a division value; and

v) for each of the at least one attribute, adjusting, with the machine, the attribute such that the adjusted attribute is a function of the division value.

13. The method of claim 12 wherein the function is a logarithmic function.

14. The method of claim 8 wherein the step of adjusting, for each of the at least one attribute of each entity of the group of entities, the attribute value associated therewith includes sub-steps of:

i) for each of the at least one attribute, over all entities of the group of entities, determining, with the machine, a number of times an attribute value of the at least one attribute belongs to a predetermined set of values to generate an attribute frequency value; and

ii) adjusting, with the machine, each of the at least one attribute such that the adjusted attribute decreases as the attribute frequency value increases,

wherein each of the at least one attribute is a value attribute.

15. The method of claim 8 wherein the step of adjusting, for each of the at least one attribute of each entity of the group of entities, the attribute value associated therewith includes sub-steps of:

i) over each of the at least one attribute, over all entities of the group of entities, determining, with the machine, a running sum of an attribute value of the at least one attribute to generate an attribute frequency value; and

ii) adjusting, with the machine, each of the at least one attribute such that the adjusted attribute decreases as the attribute frequency value increases,

wherein each of the at least one attribute is a value attribute.

16. The method of claim 1 wherein the step of determining a degree to which the new and one entities match includes a step of determining a correlation between the new and one entities based on the attribute value associated with each of the at least one attribute of the new entity and the adjusted attribute value of each of the at least one attribute of the one entity.

17. A method for operating a machine to generate a prediction of an attribute value of at least one attribute of a new entity based on at least one attribute value of at least one attribute of a group of entities, the method comprising steps of:

a) accepting, by the machine, information relating to the new entity, the group of entities and the attributes and attribute values of the new entity and the group of entities;

b) for each of the at least one attribute of each entity of the group of entities, adjusting, with the machine, the attribute value associated therewith based on a frequency of the at least one attribute over all entities of the group of entities, to generate an adjusted attribute value;

c) for each entity of the group of entities, determining, with the machine, a degree to which (i) the entity and (ii) the new entity match based on the adjusted attribute value of each of the at least one attribute of the entity and based on the attribute value associated with each of the at least one attribute of the new entity; and

d) predicting, with the machine, an attribute value of at least one of the at least one attribute of the new entity based on the degree to which (i) the entities of the group of entities and (ii) the new entity match and based on the at least one adjusted attribute value associated with the at least one attribute of the entities of the group of entities.

18. The method of claim 17 wherein the step of adjusting the attribute value associated with each of the at least one attribute of each of the entities of the group of entities includes sub-steps of:

i) for each of the at least one attribute, over all entities of the group of entities, determining, with the machine, a number of times an attribute value exists for the at least one attribute to generate an attribute frequency value; and

ii) for each entity of the group of entities and for each of the at least one attribute, adjusting, with the machine, the attribute value of the at least one attribute such that the adjusted attribute value decreases as the attribute frequency value increases.

19. The method of claim 18 wherein the attribute value is divided by the attribute frequency value to form the adjusted attribute value.

20. The method of claim 18 wherein the adjusted attribute value is an inverse function of the attribute frequency value.

21. The method of claim 17 wherein the step of adjusting, for each of the at least one attribute of each entity of the group of entities, the attribute value associated therewith includes sub-steps of:

i) for each of the at least one attribute, over all entities of the group of entities, determining, with the machine, the number of times an attribute value of the at least one attribute belongs to a predetermined set of values to generate an attribute frequency value; and

ii) for each entity of the group of entities and for each of the at least one attribute, adjusting, with the machine, the attribute value of the at least one attribute such that the adjusted attributed value decreases as the attribute frequency value increases,

wherein the at least one attribute is a value attribute.

22. The method of claim 17 wherein the step of adjusting, for each of the at least one attribute of each entity of the group of entities, the attribute value associated therewith includes sub-steps of:

i) over each of the at least one attribute, over all entities of the group of entities, determining, with the machine, a running sum of an attribute value of the at least one attribute to generate an attribute frequency value; and

ii) for each entity of the group of entities and for each of the at least one attribute, adjusting, with the machine, the attribute value of the at least one attribute such that the adjusted attribute value decreases as the attribute frequency value increases,

wherein the at least one attribute is a value attribute.

23. The method of claim 17 wherein the step of determining a degree to which (i) the new entity and (ii) the one entity match includes a sub-step of:

i) for each of the at least one attribute, if the attribute value of the at least one attribute of the new entity matches the attribute value of the at least one attribute of the one entity, then adding, with the machine, the adjusted attribute value of the at least one attribute of the one entity to a running sum,

wherein the degree to which (i) the new entity and (ii) the one entity match is based on a final value of the running sum over each of the at least one attributes.

24. The method of claim 17 wherein the step of predicting an attribute value of at least one of the at least one attribute of the new entity includes a sub-step of:

i) over all entities of the group of entities, summing, with the machine, a product of the degree to which (i) the new entity and (ii) the entity match and the adjusted attribute value of the entity to generate a predicted attribute value.

25. The method of claim 17 wherein the predicted attribute value of the at least one of the at least one attribute of the new entity represents a prediction of a degree to which the new entity will want to render particular content.

26. A method for operating a machine to generate a prediction of an attribute value of at least one attribute of a new entity based on at least one attribute value of at least one attribute of a group of entities, the method comprising steps of:

a) accepting, by the machine, information relating to the new entity, the group of entities, and the attributes and attribute values of the new entity and the group of entities;

b) for each of the at least one attribute of each entity of the group of entities, adjusting, with the machine, the attribute value associated therewith based on a frequency of the at least one attribute throughout the entities of the group of entities to thereby generate an adjusted attribute value;

c) for each of the at least one attribute of the new entity, determining, with the machine, a normalized attribute value associated with the at least one attribute value;

d) determining, with the machine, a similarity between the new entity and the one entity based on each of the at least one normalized attribute value associated with each of the at least one attribute of the new entity and each of the at least one adjusted attribute value of the at least one attribute of the one entity;

e) determining, with the machine, a case weight for each entity of the group of entities based on the similarity and a square root of a sum, over all of the at least one attribute, of the adjusted attribute value squared;

f) summing, with the machine, the case weights of each entity of the group of entities to generate a total case weight;

g) for each of the at least one attribute of each of the entities of the group of entities, determining, with the machine, a new attribute value based on the attribute value of the at least one attribute of the entity and the case weight of the entity;

h) for each of the at least one attribute, summing, with the machine, over all of the entities of the group of entities, the new attribute values to generate a new attribute value sum; and

i) predicting, with the machine, an attribute value of at least one of the at least one attribute of the new entity based on the new attribute value sum and the total case weight.

27. The method of claim 26 wherein the step of adjusting, for each of the at least one attribute of each entity of the group of entities, the attribute value associated therewith includes sub-steps of:

i) for each of the at least one attribute, over all entities of the group of entities, determining, with the machine, a number of times an attribute value exists for the at least one attribute to generate an attribute frequency value; and

ii) adjusting, with the machine, each of the at least one attribute, such that the adjusted attribute decreases as the attribute frequency value increases.

28. The method of claim 27 wherein the sub-step of adjusting each of the at least one attribute includes further steps of:

iii) determining, with the machine, a total number of entities of the group of entities;

iv) for each of the at least one attribute, dividing, with the machine, the total number of entities by the attribute frequency value to form a division value; and

v) for each of the at least one attribute, adjusting, with the machine, the attribute such that the adjusted attribute is a function of the division value.

29. The method of claim 28 wherein the function is a logarithmic function.

30. The method of claim 28 wherein the step of adjusting, for each of the at least one attribute of each entity of the group of entities, the attribute value associated therewith includes sub-steps of:

i) for each of the at least one attribute, over all entities of the group of entities, determining, with the machine, a number of times an attribute value of the at least one attribute belongs to a predetermined set of values to generate an attribute frequency value; and

ii) adjusting, with the machine, each of the at least one attribute such that the adjusted attribute decreases as the attribute frequency value increases,

wherein each of the at least one attribute is a value attribute.

31. The method of claim 28 wherein the step of adjusting, for each of the at least one attribute of each entity of the group of entities, the attribute value associated therewith includes sub-steps of:

i) over each of the at least one attribute, over all entities of the group of entities, determining, with the machine, a running sum of an attribute value of the at least one attribute to generate an attribute frequency value; and

ii) adjusting, with the machine, each of the at least one attribute such that the adjusted attribute decreases as the attribute frequency value increases,

wherein each of the at least one attribute is a value attribute.

32. The method of claim 28 wherein the step of, for each of the at least one attribute of the new entity, determining a normalized attribute value associated with the at least one attribute value includes sub-steps of:

i) for each of the at least one attribute of the new entity, determining, with the machine, an adjusted attribute value;

ii) determining, with the machine, a square root of a sum of squares of the at least one adjusted attribute value associated with the at least one attribute of the new entity; and

iii) for each of the at least one attribute of the new entity, dividing, with the machine, an associated adjusted attribute value by the square root.

33. The method of claim 28 wherein the step of determining, for each of the at least one attribute of the entities of the group of entities, a new attribute value includes a sub-step of:

i) multiplying, with the machine, the attribute value of the at least one attribute and the case weight of the entity.

34. The method of claim 28 wherein the step of predicting the attribute value of at least one of the at least one attribute of the new entity includes a sub-step of:

i) dividing, with the machine, the new attribute value sum by the total case weight.

35. An apparatus for predicting, based on records of information relating attribute values to attributes of known entities, a value of at least one attribute of a new entity, the new entity having at least one other attribute having an associated attribute value, the apparatus comprising:

a) a retriever for retrieving the records; and

b) a collaborative filter engine for predicting the value of the at least one attribute of the new entity based on attribute values of attributes of the known entities in the records and the attribute value associated with the at least one other attribute of the new entity, wherein the prediction of the collaborative filter engine considers an inverse of a frequency of the attribute in the records of the known entities.

36. The apparatus of claim 35 wherein the collaborative filter engine:

a) for each of the attribute values of the attributes of the known entities, adjusts the attribute value based on the frequency of the attribute, to generate adjusted attribute values;

b) for each entity of the known entities, determines a degree to which (i) the entity and (ii) the new entity match based on the adjusted attribute values of the entity and the attribute value associated with the at least one other attribute of the new entity; and

c) predicts the attribute value of the at least one attribute of the new entity based on the degree to which (i) the known entities and (ii) the new entity match and based on the adjusted attribute values of the attributes of the known entities.

37. The apparatus of claim 36 wherein the collaborative filter engine adjusts the attribute values associated with the at least one attribute of each of the known entities by:

i) for each of the at least one attribute, over all of the known entities, determining a number of times an attribute value exists for the at least one attribute to generate an attribute frequency value; and

ii) for each of the known entities and for each of the at least one attribute, adjusting the attribute value of the at least one attribute such that the adjusted attribute value decreases as the attribute frequency value increases.

38. The apparatus of claim 37 wherein the attribute value is divided by the attribute frequency value to form the adjusted attribute value.

39. The apparatus of claim 37 wherein the adjusted attribute value is an inverse function of the attribute frequency value.

40. The apparatus of claim 36 wherein the collaborative filter engine adjusts, for each of the at least one attribute of each of the known entities, the attribute value associated therewith by:

i) for each of the at least one attribute, over all of the known entities, determining the number of times an attribute value of the at least one attribute belongs to a predetermined set of values to generate an attribute frequency value; and

ii) for each of the known entities and for each of the at least one attribute, adjusting the attribute value of the at least one attribute such that the adjusted attribute value decreases as the attribute frequency value increases,

wherein the at least one attribute is a value attribute.

41. The apparatus of claim 36 wherein the collaborative filter engine adjusts, for each of the at least one attribute of each of the known entities, the attribute value associated therewith by:

i) over each of the at least one attribute, over all of the known entities, determining a running sum of an attribute value of the at least one attribute to generate an attribute frequency value; and

ii) for each of the known entities and for each of the at least one attribute, adjusting the attribute value of the at least one attribute such that the adjusted attribute value decreases as the attribute frequency value increases,

wherein the at least one attribute is a value attribute.

42. The apparatus of claim 36 wherein the collaborative filter engine determines a degree to which (i) the new entity and (ii) the one entity match by:

i) for each of the at least one attribute, if the attribute value of the at least one attribute of the new entity matches the attribute value of the at least one attribute of the one entity, then adding the adjusted attribute value of the at least one attribute of the one entity to a running sum,

wherein the degree to which (i) the new entity and (ii) the one entity match is based on a final value of the running sum over each of the at least one attributes.

43. The apparatus of claim 36 wherein the collaborative filter engine predicts an attribute value of at least one of the at least one attribute of the new entity by:

i) over all of the known entities, summing a product of the degree to which (i) the new entity and (ii) the entity match and the adjusted attribute value of the entity to generate a predicted attribute value.

44. The apparatus of claim 36 wherein the predicted attribute value of the at least one of the at least one attribute of the new entity represents a prediction of a degree to which the new entity will want to consume particular content.

45. The apparatus of claim 35 wherein the collaborative filter engine (a) adjusts, for each of the at least one attribute of each of the known entities, the attribute value associated therewith based on the frequency of the at least one attribute throughout the known entities to thereby generate an adjusted attribute value;

(b) for each of the at least one attribute of the new entity, determines a normalized attribute value associated with the at least one attribute value;

(c) determines a similarity between the new entity and the one entity based on each of the at least one normalized attribute value associated with each of the at least one attribute of the new entity and each of the at least one adjusted attribute value of the at least one attribute of the one entity;

(d) determines a case weight for each entity of the known entities based on the similarity and a square root of a sum, over all of the at least one attribute, of the adjusted attribute value squared;

(e) sums the case weights of each of the known entities to generate a total case weight;

f) for each of the at least one attribute of each of the known entities, determines a new attribute value based on the attribute value of the at least one attribute of the entity and the case weight of the entity;

(g) for each of the at least one attribute, sums, over all of the known entities, the new attribute values to generate a new attribute value sum; and

(h) predicts an attribute value of at least one of the at least one attribute of the new entity based on the new attribute value sum and the total case weight.

46. The apparatus of claim 45 wherein the collaborative filter engine adjusts, for each of the at least one attribute of each entity of the known entities, the attribute values associated therewith by:

i) for each of the at least one attribute, over all of the known entities, determining a number of times an attribute value exists for the at least one attribute to generate an attribute frequency value; and

ii) adjusting each of the at least one attribute such that the adjusted attribute decreases as the attribute frequency value increases.

47. The method of claim 46 wherein the sub-step of adjusting each of the at least one attribute includes further steps of:

iii) determining a total number of the known entities;

iv) for each of the at least one attribute, dividing the total number of the known entities by the attribute frequency value to form a division value; and

v) for each of the at least one attribute, adjusting the attribute value such that the adjusted attribute value is a function of the division value.

48. The method of claim 47 wherein the function is a logarithmic function.

49. The apparatus of claim 46 wherein the collaborative filter engine adjusts, for each of the at least one attribute of each of the known entities, the attribute value associated therewith by:

i) over each of the at least one attribute, over all of the known entities, determining a running sum of an attribute value of the at least one attribute to generate an attribute frequency value; and

ii) adjusting each of the at least one attribute such that the adjusted attribute decreases as the attribute frequency value increases,

wherein each of the at least one attribute is a value attribute.

50. The apparatus of claim 45 wherein the collaborative filter engine adjusts, for each of the at least one attribute of each of the known entities, the attribute value associated therewith by:

i) for each of the at least one attribute, over all of the known entities, determining the number of times an attribute value of the at least one attribute falls within a predetermined range to generate an attribute frequency value; and

ii) adjusting each of the at least one attribute such that the adjusted attribute decreases as the attribute frequency value increases,

wherein each of the at least one attribute is a value attribute.

51. The apparatus of claim 45 wherein the improved collaborative filter, for each of the at least one attribute of the new entity, determines a normalized attribute value associated with the at least one attribute value by:

i) for each of the at least one attribute of the new entity, determining an adjusted attribute value;

ii) determining a square root of a sum of squares of the at least one adjusted attribute value associated with the at least one attribute of the new entity; and

iii) for each of the at least one attribute of the new entity, dividing an associated adjusted attribute value by the square root.

52. The apparatus of claim 35 wherein, for each of the at least one attribute of the known entities, the collaborative filter determines a new attribute value by multiplying the attribute value of the at least one attribute and the case weight of the entity.

53. The apparatus of claim 35 wherein the collaborative filter process predicts the attribute value of at least one of the at least one attribute of the new entity by dividing the new attribute value sum by the total case weight.

54. The apparatus of claim 35 wherein the retriever for retrieving the records is located at a server, and wherein the collaborative filter engine is located at a client and further comprising:

d) a network for permitting communication of data between the client and the server.

55. The apparatus of claim 54 wherein the client includes

A) a processor,

B) a storage device,

C) an input/output interface,

D) a system bus used by the processor, the storage device of the client and the input/output interface,

E) an input device coupled with the input/output interface, and

F) an output device coupled with the input/output interface.

56. The apparatus of claim 55 wherein the client effects a browser process and an input/output interface process.

57. The apparatus of claim 56 wherein the browser process is effected by the processor executing instructions.

58. The apparatus of claim 56 wherein the browser process includes a navigation process, a user interface process, and a collaborative filter process, and wherein the collaborative filter engine is the processor executing instructions for effecting the collaborative filter process.

59. The apparatus of claim 58 wherein the user interface process of the browser process effects a graphical user interface on the output device to provide a display having a content display area and a content suggestion area.

60. The apparatus of claim 59 wherein the predicted attribute value of the at least one attribute represents content that the client may wish to consume.

61. The apparatus of claim 60 wherein the content suggestion area includes a hyper-text link to the content that the client may wish to consume.

62. The apparatus of claim 54 wherein the network is the Internet.

63. The apparatus of claim 54 wherein the client is identified as an entity with a cookie.

64. The apparatus of claim 54 wherein the client includes an input/output interface and a browser having a collaborative filter, a navigator, and a user interface, and

wherein the server includes a content transfer facility and an entity/attribute record retriever.

65. The apparatus of claim 64 wherein when a user, via the user interface, submits a content request to the navigator:

i) the navigator will submit a request for the content, an identification of the client, and an indication of collaborative filtering capability of the content transfer facility of the server;

ii) the content transfer facility of the server will submit a request for the content;

iii) the content transfer facility of the server will submit a request to the entity/attribute record retriever for records;

iv) the entity/attribute record retriever will return a sample of records to the content transfer facility;

v) the content transfer facility of the server will return the requested content and the sample of records to the navigator of the client;

vi) the navigator of the client will provide the content of the user interface;

vii) the navigator of the client will provide the sample records to the collaborative; and

viii) the collaborative filter will provide suggested content to the user interface.

66. A machine-readable medium having machine-executable instructions which, when executed by the machine, perform a method for operating a machine to generate a determination of a degree to which (i) a new entity having at least one attribute with an associated attribute value, and (ii) one entity selected from a group of entities, each entity of the group of entities having at least one attribute with an associated attribute value, match, the method comprising steps of:

a) accepting, by the machine, information relating to the new entity, the entities of the group of entities, and the attributes and attribute values of the new entity and the entities of the group of entities;

b) for each of the at least one attribute of each entity of the group of entities, adjusting, with the machine, the attribute value associated therewith based on a frequency of the at least one attribute throughout the entities of the group of entities to thereby generate an adjusted attribute value; and

c) determining, with the machine, a degree to which (i) the new entity and (ii) the one entity match based on the attribute value associated with each of the at least one attribute of the new entity and the adjusted attribute value of each of the at least one attribute of the one entity.

67. A method comprising a step of communicating machine-executable instructions which, when executed by the machine, perform a method for operating a machine to generate a determination of a degree to which (i) a new entity having at least one attribute with an associated attribute value, and (ii) one entity selected from a group of entities, each entity of the group of entities having at least one attribute with an associated attribute value, match, the method comprising steps of:

a) accepting, by the machine, information relating to the new entity, the entities of the group of entities, and the attributes and attribute values of the new entity and the entities of the group of entities;

b) for each of the at least one attribute of each entity of the group of entities, adjusting, with the machine, the attribute value associated therewith based on a frequency of the at least one attribute throughout the entities of the group of entities to thereby generate an adjusted attribute value;

c) determining, with the machine, a degree to which (i) the new entity and (ii) the one entity match based on the attribute value associated with each of the at least one attribute of the new entity and the adjusted attribute value of each of the at least one attribute of the one entity.