Listings optimization using a plurality of data sources

• US 7,617,203 B2
• Filed: 01/06/2004
• Issued: 11/10/2009
• Est. Priority Date: 08/01/2003
• Status: Active Grant

• Current Assignee: R2 Solutions LLC (Acacia Research Corporation)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Gerster, David A., Cadogan, Timothy Roy, Awadallah, Amr, Diab, Ali
• Primary Examiner(s): Jalil; Neveen Abel
• Assistant Examiner(s): Radtke; Mark Andrew X
• Application Number:
  US10/752,742
• Publication Number:
  US 20050027699A1
• Time in Patent Office: 2,135 Days
• Field of Search: None
• 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: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: Y10S 707/99935 Query augmenting and refining, e.g. inexact access

Abstract

A system is provided for allocating combinations of search results, types of space, and/or other information from different sources (e.g., search engines) in which a type of space, search results, and/or other information from at least one source or type or from each source or type, for example, are optimized to obtain an optimum commercial value. Using the example of a search, a commercial metric and a user satisfaction metric are established for search terms and used in the optimization process. In calculating the commercial value and the user satisfaction value for a set of search results, the weight given to the commercial value and the user satisfaction value of a search result is different depending on its source. Optionally, keeping the user satisfaction value above a certain threshold is treated as a constraint while optimizing the commercial value. Alternatively, a tradeoff may be allowed between the minimum threshold for the user satisfaction and a better commercial value. For example, a commercial value may be associated with the commercial metric and quality metric so that the total commercial value may be calculated and optimized.

Claims

1. A method comprising:

receiving a query;

receiving a plurality of items from a plurality of candidate sources;

generating an initial set of possible composite search results, each of which is a different composition of items from the plurality of candidate sources;

determining a first estimated attribute value and a second estimated attribute value for each possible composite search result in the initial set of possible composite search results;

filtering the initial set of possible composite search results based upon whether the first estimated attribute value satisfies a specified threshold value to generate a filtered set;

selecting a final composite search result from the filtered set where the second estimated attribute value is greatest; and

providing for display at a client the final composite search result as the answer to said query,

wherein one of the estimated attribute values is a commercial value and the other estimated attribute value is a user satisfaction value, and

wherein the method is performed by one or more computing devices.

2. The method of claim 1, wherein the first estimated attribute value satisfies a first specified threshold when the first estimated attribute value is less than the threshold value.

3. The method of claim 1, wherein the first estimated attribute value satisfies a first specified threshold when the first estimated attribute value is greater than the threshold value.

4. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the method recited in claim 1.

5. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the method recited in claim 2.

6. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the method recited in claim 3.

7. The method of claim 1, wherein the final composite search result is displayed with results from different candidate sources integrated and the candidate source for each item labeled.

8. The method of claim 1, wherein the final composite search result is displayed without identifying the candidate source for each item.

9. The method of claim 1, wherein each estimated attribute value is determined on a term-by-term basis.

10. The method of claim 1, wherein one of the estimated attribute values is calculated based upon whether a user makes a purchase.

11. The method of claim 1, wherein an extremization process is used to optimize an at least one of the estimated attribute values, wherein the extremization process maximizes or minimizes a function of the estimated attribute.

12. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the method recited in claim 7.

13. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the method recited in claim 8.

14. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the method recited in claim 9.

15. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the method recited in claim 10.

16. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the method recited in claim 11.

17. The method of claim 1, wherein one of the estimated attribute values is associated with an estimated market share that is an estimated amount of sponsored items received.

18. The method of claim 1, wherein one of the estimated attribute values is associated with name recognition.

19. The method of claim 1, wherein one of the estimated attribute values is associated with a monetary value.

20. The method of claim 1, wherein the items comprise items that are sponsored by at least one of the plurality of candidate sources.

21. The method of claim 1, wherein filtering the initial set of composite search results further comprises determining whether the second estimated attribute value satisfies a second specified threshold;

upon determining that the second estimated attribute satisfies a second specified threshold, adjusting the first specified threshold so that fewer composite search results are filtered.

22. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the method recited in claim 17.

23. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the method recited in claim 18.

24. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the method recited in claim 19.

25. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the method recited in claim 20.

26. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the method recited in claim 21.

27. A method comprising:

receiving a query;

receiving a plurality of items from a plurality of candidate sources;

generating a plurality of item groups, each of which is a different composition of items from the plurality of candidate sources;

determining a first estimated attribute value and a second estimated attribute value for each item group in the plurality of item groups;

selecting a final item group from the plurality of item sets based upon first estimated attribute values and second estimated attribute values for each item group in the plurality of item groups; and

providing, for display at a client, the final item group as an answer to said query,

wherein one of the estimated attribute values is a commercial value and the other estimated attribute value is a quality value, and

wherein the method is performed by one or more computing devices.

28. The method of claim 27, wherein a first item set of the plurality of item sets contains more items from a first candidate source of the plurality of candidate sources than items from a second candidate source of the plurality of candidate sources;

and

wherein a second item set of the plurality of item sets contains more items from the second candidate source than items from the first candidate source.

29. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the method recited in claim 27.

30. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the method recited in claim 28.

31. A method comprising:

receiving a query;

receiving, based upon the query, a plurality of items from a plurality of candidate sources;

generating an initial set of item groups, where each item group in the initial set of item groups is a different composition of items from the plurality of candidate sources;

determining a commercial value, that is a measure of the commercial nature of the query, and a quality value, that is an expected measure of customer satisfaction with the items, for each item group in the initial set of item groups;

filtering the initial set of item groups based upon whether the quality value is greater than a specified threshold value to generate a filtered set;

selecting a final item group from the filtered set where the commercial value is greatest; and

providing, for display at a client, the final item group as an answer to said query,

wherein the method is performed by one or more computing devices.

32. A computer-readable storage medium storing one or more sequences of instructions which, when executed by one or more processors, cause the one or more processors to perform the method recited in claim 31.