RANKING ALGORITHM FOR SEARCH OUERIES

• US 20140214817A1
• Filed: 03/30/2014
• Published: 07/31/2014
• Est. Priority Date: 03/31/2009
• Status: Active Grant

• Current Assignee: eBay Inc.
• Original Assignee: eBay Inc.
• Inventors: Hu, Wenyan, Bolivar, Alvaro, Shoup, Randall Scott, Zhang, Xiaodi
• Granted Patent: US 9,424,317 B2
• Time in Patent Office: Days
• US Class Current: 707/723
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/3338 Query expansion
• CPC Class Codes: G06F 16/334 Query execution G06F16/335 takes precedence
• CPC Class Codes: G06F 16/90324 using system suggestions

Abstract

In various embodiments, a method of prioritizing search results in an electronic environment is disclosed. The method includes selecting a plurality of equivalent keywords responsive to a search query from an end-user, determining a rank of each of the plurality of equivalent keywords, selecting a plurality of most highly ranked keywords from the plurality of equivalent keywords, and preparing a response including the plurality of most highly ranked keywords.

Claims

1. A method, comprising:

selecting a plurality of equivalent keywords responsive to a search query;

determining a rank of each of the plurality of equivalent keywords;

selecting a plurality of most highly ranked keywords from the plurality of equivalent keywords; and

preparing a response including the plurality of most highly ranked keywords.

2. The method of claim 1, further comprising transmitting the response.

3. The method of claim 2, further comprising fitting the response within a single communications packet prior to transmitting the response

4. The method of claim 1, wherein the selecting the plurality of equivalent keywords is based on one or more characters within the search query.

5. The method of claim 1, wherein the one or more characters are received within a single packet.

6. The method of claim 1, further comprising basing the rank on a turnover rate of a listing to which the search query is directed.

7. The method of claim 1, wherein the determining of the rank includes calculating a weight of each of the plurality of equivalent keywords.

8. The method of claim 6, further comprising basing the weighting on at least one item in a group of parameters, the parameters consisting of most frequent queries, a number of items available matching the search query, a number of bids on items matching the search query, a number of purchases of items matching the search query, and a number of items matching the search query being placed on a watch list.

9. The method of claim 1, further comprising selecting the plurality of equivalent keywords from a weighted database.

10. The method of claim 1, wherein selecting the plurality of equivalent keywords responsive to the search query includes finding prefixes or infixes to match available keywords from one or more consecutive characters from the search query.

11. A method, comprising:

receiving one or more characters from an end-user as a query;

selecting a plurality of equivalent keywords responsive to the query, the plurality of equivalent keywords being selected based on a consideration of matching at least a portion of the one or more characters both as a prefix and an infix;

evaluating each of the plurality of equivalent keywords based on a probability of matching the query of the end-user;

preparing a subset of the plurality of equivalent keywords based on the matching probability, the subset forming a response; and

transmitting the response to the end-user.

12. The method of claim 11, further comprising selecting the plurality of equivalent keywords from a weighted database.

13. The method of claim 12, further comprising updating the database based on a determination of a positive matching of at least one of the subset of the plurality of keywords.

14. The method of claim 13, wherein the updating includes increasing a weighting factor for the at least one of the subset of the plurality of keywords.

15. The method of claim 11, wherein preparing the subset to form the response is further based on selecting a plurality of most highly ranked keywords from the plurality of equivalent keywords based on the matching probability.

16. The method of claim 15, further comprising basing a rank of the plurality of most highly ranked keywords on a turnover rate of a listing to which the search query is directed.

17. The method of claim 16, wherein the determining of the rank includes calculating a weight of each of the plurality of most highly ranked keywords.

18. A tangible machine-readable storage medium having no transitory signal components and storing instructions that, when executed by one or more processors, causes the one or more processors to perform operations, comprising:

selecting a plurality of equivalent keywords responsive to a search query;

determining a rank of each of the plurality of equivalent keywords;

selecting a plurality of most highly ranked keywords from the plurality of equivalent keywords; and

preparing a response including the plurality of most highly ranked keywords.

19. The tangible machine-readable storage medium of claim 18, wherein the determining of the rank includes calculating a weight of each of the plurality of equivalent keywords.

20. The tangible machine-readable storage medium of claim 19, further comprising basing the weighting on at least one item in a group of parameters, the parameters consisting of most frequent queries, a number of items available matching the search query, a number of bids on items matching the search query, a number of purchases of items matching the search query, and a number of items matching the search query being placed on a watch list.