DETERMINING SEARCH RESULT RANKINGS BASED ON TRUST LEVEL VALUES ASSOCIATED WITH SELLERS

• US 20140236942A1
• Filed: 02/20/2013
• Published: 08/21/2014
• Est. Priority Date: 02/22/2012
• Status: Active Grant

• Current Assignee: Alibaba Group Holding Ltd.
• Original Assignee: Alibaba Group Holding Ltd.
• Inventors: Li, Jiasen
• Granted Patent: US 9,311,650 B2
• Time in Patent Office: Days
• US Class Current: 707/735
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

Adjusting search results ranking is disclosed, including: receiving a search query comprising one or more keywords submitted by a user; determining intermediate ranked results comprising a plurality of sets of product information matching the one or more keywords; determining a trust level value associated with the user with respect to a first seller of a plurality of sellers associated with the intermediate ranked results, wherein the trust level value is determined based at least in part on one or more historical user product information evaluation records associated with the first seller submitted by the user; and adjusting ranking associated with the intermediate ranked results based at least in part on the determined trust level value associated with the user with respect to the first seller to determine final ranked results.

Claims

1. A system to adjust search results ranking, comprising:

one or more processors configured to;

receive a search query comprising one or more keywords submitted by a user;

determine intermediate ranked results comprising a plurality of sets of product information matching the one or more keywords;

determine a trust level value associated with the user with respect to a first seller of a plurality of sellers associated with the intermediate ranked results, wherein the trust level value is determined based at least in part on one or more historical user product information to evaluation records associated with the first seller submitted by the user; and

adjust ranking associated with the intermediate ranked results based at least in part on the determined trust level value associated with the user with respect to the first seller to determine final ranked results; and

one or more memories coupled to the one or more processors and configured to provide the one or more processors with instructions.

2. The system of claim 1, wherein the intermediate ranked results are associated with a first ranking, wherein the first ranking is determined based at least in part on index term weights associated with search results included in the intermediate ranked results.

3. The system of claim 1, wherein the intermediate ranked results are associated with a first ranking, wherein the first ranking is determined based at least in part on composite scores associated with search results included in the intermediate ranked results.

4. The system of claim 1, wherein a first portion of the intermediate ranked results associated with a predetermined number of search results is retained and a second portion of the intermediate ranked results beyond the predetermined number of search results is discarded to determine the final ranked results.

5. The system of claim 1, wherein identification information of the user is determined based at least on one or more of the following:

a logged on status associated with the user and data associated with a cookie stored at a device associated with the user.

6. The system of claim 5, wherein the one or more historical user product information evaluation records associated with the first seller is determined based at least in part on the identification information of the user.

7. The system of claim 1, wherein the one or more processors are further configured to:

determine whether the trust level value exceeds a predetermined trust level threshold value; and

in the event that the trust level value exceeds the predetermined trust level threshold value, add identification information associated with the first seller onto a white list and in the event that the trust level value does not exceed the predetermined trust level threshold value, add identification information associated with the first seller onto a black list.

8. The system of claim 7, wherein the ranking associated with the intermediate ranked results is adjusted based on the white list and the black list.

9. The system of claim 8, wherein a first search result of the intermediate ranked results associated with a seller on the white list is determined to be ranked higher among a second ranking associated with the final ranked results than a second search result of the intermediate ranked results associated with a seller on the black list.

10. The system of claim 1, wherein the trust level value is determined based at least in part on performing an averaging function with respect to values corresponding to the one or more historical user product information evaluation records.

11. A method to adjust search results ranking, comprising:

receiving a search query comprising one or more keywords submitted by a user;

determining intermediate ranked results comprising a plurality of sets of product information matching the one or more keywords;

determining a trust level value associated with the user with respect to a first seller of a plurality of sellers associated with the intermediate ranked results, wherein the trust level value is determined based at least in part on one or more historical user product information evaluation records associated with the first seller submitted by the user; and

adjusting ranking associated with the intermediate ranked results based at least in part on the determined trust level value associated with the user with respect to the first seller to determine final ranked results.

12. The method of claim 11, wherein the intermediate ranked results are associated with a first ranking, wherein the first ranking is determined based at least in part on index term weights associated with search results included in the intermediate ranked results.

13. The method of claim 11, wherein the intermediate ranked results are associated with a first ranking, wherein the first ranking is determined based at least in part on composite scores associated with search results included in the intermediate ranked results.

14. The method of claim 11, wherein a first portion of the intermediate ranked results associated with a predetermined number of search results is retained and a second portion of the intermediate ranked results beyond the predetermined number of search results is discarded to determine the final ranked results.

15. The method of claim 11, wherein identification information of the user is determined is based at least on one or more of the following:

a logged on status associated with the user and data associated with a cookie stored at a device associated with the user.

16. The method of claim 15, wherein the one or more historical user product information evaluation records associated with the first seller is determined based at least in part on the identification information of the user.

17. The method of claim 11, further comprising:

determining whether the trust level value exceeds a predetermined trust level threshold value; and

in the event that the trust level value exceeds the predetermined trust level threshold value, adding identification information associated with the first seller onto a white list and in the event that the trust level value does not exceed the predetermined trust level threshold value, adding identification information associated with the first seller onto a black list.

18. The method of claim 17, wherein the ranking associated with the intermediate ranked results is adjusted based on the white list and the black list.

19. The method of claim 18, wherein a first search result of the intermediate ranked results associated with a seller on the white list is determined to be ranked higher among a second ranking associated with the final ranked results than a second search result of the intermediate ranked results associated with a seller on the black list.

20. The method of claim 11, wherein the trust level value is determined based at least in part on performing an averaging function with respect to values corresponding to the one or more historical user product information evaluation records.

21. A computer program product for adjusting search results ranking, the computer program product being embodied in a computer readable storage medium and comprising computer instructions for:

receiving a search query comprising one or more keywords submitted by a user;

determining intermediate ranked results comprising a plurality of sets of product information matching the one or more keywords;

determining a trust level value associated with the user with respect to a first seller of a plurality of sellers associated with the intermediate ranked results, wherein the trust level value is determined based at least in part on one or more historical user product information evaluation records associated with the first seller submitted by the user; and

adjusting ranking associated with the intermediate ranked results based at least in part on the determined trust level value associated with the user with respect to the first seller to determine final ranked results.