Search method and system and system using the same

• US 7,461,051 B2
• Filed: 11/10/2003
• Issued: 12/02/2008
• Est. Priority Date: 11/11/2002
• Status: Expired due to Fees

• Current Assignee: Transparensee Systems, Inc.
• Original Assignee: Transparensee Systems, Inc.
• Inventors: Lavine, Steven David
• Primary Examiner(s): Corrielus; Jean M.
• Assistant Examiner(s): COLAN, GIOVANNA B
• Application Number:
  US10/534,627
• Publication Number:
  US 20060149708A1
• Time in Patent Office: 1,849 Days
• Field of Search: 705/10, 707/3, 707/4, 707/1, 707/5
• US Class Current: 1/1
• CPC Class Codes: G06F 16/2455 Query execution
• CPC Class Codes: G06F 16/954 Navigation, e.g. using categorised browsing
• CPC Class Codes: Y10S 707/99931 Database or file accessing
• CPC Class Codes: Y10S 707/99933 Query processing, i.e. searching
• CPC Class Codes: Y10S 707/99934 Query formulation, input preparation, or translation
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access

Abstract

Information regarding the structure of information in a content database is maintained in a structure database. The structure database is used to correlate the data structure of a query to the structure of the content database, in order to determine that information in the content database which needs to be provided to a searcher in response to the query. In one embodiment, this search method is used in an online forum, and the forum maintains a reputation score for users with respect to given subject matter. The reputation score is dependent upon the quality of a user'"'"'s participation in the forum. A user'"'"'s reputation score depends upon the evaluation by others of information he posts and upon the user evaluating information posted by others.

Claims

1. A method for searching a content database stored in computer storage, the content database including a plurality of records each containing multiple fields of information, the method comprising the steps of:

maintaining a structure database in computer storage in which each record is parsed into one or more record categories, each record category having zero or more sub-categories and one or more fields of information, the structure database containing, for each record category, information defining a data structure of the record category;

receiving a search query comprising one or more query categories, each query category comprising zero or more sub-categories and one or more selections from a user;

determining for each query category, a data structure of the query category based on the data structure of a corresponding record category;

for each of one or more records, performing a correlation between the data structure of each query category and the data structure of the corresponding record category to produce a relevance value for the record, wherein performing the correlation comprises;

for each data structure of a query category, generating a selection tree comprising a node representing the query category, sub-nodes representing the sub-categories and selections, and weights for each node and sub-node assigned based on the selections from the user, and

for each data structure of the corresponding record category, generating a data tree comprising a node representing the record category, sub-nodes representing the sub-categories and fields of information, and weights for each node and sub-node assigned based on the level of the node or sub-node in the data tree or based on the selections from the user, and using a correlation algorithm to correlate the weights of the data tree with the weights of the selection tree to produce a relevance value for the corresponding record category; and

as a response to the search query, selecting records in the content database based upon the relevance values for the one or more records.

2. The method of claim 1 wherein the relevance value for the corresponding record category indicates a degree of similarity between the weights of the data tree and the weights of the selection tree.

3. The method of claim 1 wherein the correlation algorithm comprises a first correlation algorithm for a first type of data structure of a category and a second correlation algorithm for a second type of data structure of a category, wherein the first and second correlation algorithms comprise different algorithms.

17. The method of claim 1, wherein selecting records in the content database comprises selecting any records that have exact matches of the selections from the user and any records that have similar but not exact matches of the selections from the user.

18. The method of claim 2, wherein the relevance value for the record comprises a combination of two or more relevance values for two or more corresponding record categories.

19. The method of claim 3, wherein:

the first type of data structure of a category comprises a hierarchical structure comprising one or more sub-categories; and

the second type of data structure of a category comprises a scalar structure comprising zero sub-categories.

20. The method of claim 19, wherein, for a corresponding record category having the first type of data structure, the generated data tree comprises weights for each node and sub-node assigned based on the level of the node or sub-node in the data tree.

21. The method of claim 19, wherein the first correlation algorithm comprises a cosine coefficient algorithm.

22. The method of claim 19, wherein, for a corresponding record category having the second type of data structure, the generated data tree comprises weights for each node and sub-node assigned based on the selections from the user.

4. A system for searching a content database stored in computer storage, the content database including a plurality of records each containing multiple fields of information, the system comprising:

a structure database in computer storage in which each record is parsed into one or more record categories, each record category having zero or more sub-categories and one or more fields of information, the structure database containing, for each record category, information defining a data structure of the record category;

a receiver for receiving a search query comprising one or more query categories, each query category comprising zero or more sub-categories and one or more selections from a user;

a determining device for determining, for each query category, a data structure of the query category based on the data structure of a corresponding record category;

a correlation device for performing, for each of one or more records, a correlation between the data structure of each query category and the data structure of the corresponding record category to produce a relevance value for the record, wherein performing the correlation comprises;

for each data structure of a query category, generating a selection tree comprising a node representing the query category, sub-nodes representing the sub-categories and selections, and weights for each node and sub-node assigned based on the selections from the user, and

for each data structure of the corresponding record category, generating a data tree comprising a node representing the record category, sub-nodes representing the sub-categories and fields of information, and weights for each node and sub-node assigned based on the level of the node or sub-node in the data tree or based on the selections from the user, and using a correlation algorithm to correlate the weights of the data tree with the weights of the selection tree to produce a relevance value for the corresponding record category; and

a response unit for responding to the search query by selecting and providing records in the content database based upon the relevance values for the one or more records.

5. The system of claim 4 wherein the relevance value for the corresponding record category indicates a degree of similarity between the weights of the data tree and the weights of the selection tree.

6. The system of claim 4 wherein the correlation algorithm comprises a first correlation algorithm for a first type of data structure of a category and a second correlation algorithm for a second type of data structure of a category, wherein the first and second correlation algorithms comprise different algorithms.

7. The system of claim 4 provided with access to a network, the content database being accessible from the network, the receiver and response unit communicating over the network.

8. The system of claim 7 wherein the content database is accessed through the network.

23. The system of claim 4, wherein selecting records in the content database comprises selecting any records that have exact matches of the selections from the user and any records that have similar but not exact matches of the selections from the user.

24. The system of claim 5, wherein the relevance value for the record comprises a combination of two or more relevance values for two or more corresponding record categories.

25. The system of claim 6, wherein:

the first type of data structure of a category comprises a hierarchical structure comprising one or more sub-categories; and

the second type of data structure of a category comprises a scalar structure comprising zero sub-categories.

26. The system of claim 25, wherein, for a corresponding record category having the first type of data structure, the generated data tree comprises weights for each node and sub-node assigned based on the level of the node or sub-node in the data tree.

27. The system of claim 25, wherein the first correlation algorithm comprises a cosine coefficient algorithm.

28. The system of claim 25, wherein, for a corresponding record category having the second type of data structure, the generated data tree comprises weights for each node and sub-node assigned based on the selections from the user.

9. In an online user forum of the type permitting communication among a plurality of users and also permitting users to post information content for access by users, the improvement comprising a reputation module storing a reputation rating for a user in association with information content, a user'"'"'s reputation being a function of the degree of his participation in the forum, said reputation module being included within a system for searching a content database stored in computer storage, the content database including a plurality of records each containing multiple fields of information, the system further comprising:

a structure database in computer storage in which each record is parsed into one or more record categories, each record category having zero or more sub-categories and one or more fields of information, the structure database containing, for each record category, information defining a data structure of the record category;

a receiver for receiving a search query comprising one or more query categories, each query category comprising zero or more sub-categories and one or more selections from a user;

a determining device for determining, for each query category, a data structure of the query category based on the data structure of a corresponding record category;

a correlation device for performing, for each of one or more records, a correlation between the data structure of each query category and the data structure of the corresponding record category to produce a relevance value for the record, wherein performing the correlation comprises;

for each data structure of a query category, generating a selection tree comprising a node representing the query category, sub-nodes representing the sub-categories and selections, and weights for each node and sub-node assigned based on the selections from the user, and

for each data structure of the corresponding record category, generating a data tree comprising a node representing the record category, sub-nodes representing the sub-categories and fields of information, and weights for each node and sub-node assigned based on the level of the node or sub-node in the data tree or based on the selections from the user, and using a correlation algorithm to correlate the weights of the data tree with the weights of the selection tree to produce a relevance value for the corresponding record category; and

a response unit for responding to the search query by selecting and providing records in the content database based upon the relevance values for the one or more records.

10. The forum of claim 9 wherein the reputation module is constructed so that a first user'"'"'s reputation rating is dependent upon the evaluation by other users of the information posted by the first user.

11. The forum of claim 9 wherein the reputation module is constructed so that a first user'"'"'s reputation rating is dependent upon his evaluation of information posted by other users.

12. The forum of claim 9 wherein the reputation module is constructed so that a first user'"'"'s reputation rating is dependent more on the evaluation by other users of the information posted by the first user than upon the first user'"'"'s evaluation of information posted by other users.

13. The forum of claim 9 wherein the relevance value for the corresponding record category indicates a degree of similarity between the weights of the data tree and the weights of the selection tree.

14. The forum of claim 9 wherein the correlation algorithm comprises a first correlation algorithm for a first type of data structure of a category and a second correlation algorithm for a second type of data structure of a category, wherein the first and second correlation algorithms comprise different algorithms.

15. The forum of claim 9 provided with access to a network, the content database being accessible from the network, the receiver and response unit communicating over the network.

16. The forum of claim 15 wherein the content database is accessed through the network.

29. The forum of claim 9, wherein selecting records in the content database comprises selecting any records that have exact matches of the selections from the user and any records that have similar but not exact matches of the selections from the user.

30. The forum of claim 13, wherein the relevance value for the record comprises a combination of two or more relevance values for two or more corresponding record categories.

31. The forum of claim 14, wherein:

the first type of data structure of a category comprises a hierarchical structure comprising one or more sub-categories; and

the second type of data structure of a category comprises a scalar structure comprising zero sub-categories.

32. The forum of claim 31, wherein, for a corresponding record category having the first type of data structure, the generated data tree comprises weights for each node and sub-node assigned based on the level of the node or sub-node in the data tree.

33. The forum of claim 31, wherein the first correlation algorithm comprises a cosine coefficient algorithm.

34. The forum of claim 31, wherein, for a corresponding record category having the second type of data structure, the generated data tree comprises weights for each node and sub-node assigned based on the selections from the user.