Querying of reputation scores in reputation systems

• US 9,330,125 B2
• Filed: 04/23/2015
• Issued: 05/03/2016
• Est. Priority Date: 03/17/2014
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: LinkedIn Corporation (Microsoft Corporation)
• Inventors: Rodriguez, Mario S., Ha, Viet Thuc, Zuniga, Jessica V., Bastian, Mathieu, Conover, Michael
• Primary Examiner(s): PENG, HUAWEN A
• Application Number:
  US14/694,958
• Publication Number:
  US 20150261759A1
• Time in Patent Office: 376 Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/22 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

The disclosed embodiments provide a reputation system. The reputation system includes a ranking apparatus that obtains a set of reputation scores for one or more dimensions of a set of items in the reputation system and generates a ranking of the items based on the reputation scores and the one or more quantiles. The reputation system also includes a query-processing apparatus that obtains a query comprising the one or more dimensions and one or more quantiles associated with the one or more dimensions and provides the ranking in a response to the query.

Claims

1. A computer-implemented method for querying a reputation system to rank a set of items, comprising:

obtaining a query comprising one or more dimensions and one or more weights associated with the one or more dimensions, wherein the query further comprises one or more quantiles associated with the one or more dimensions, wherein the dimensions comprise skills and the items comprise users, wherein the quantiles specify skill levels desired for the users, and wherein the weights specify importance of the skills;

obtaining a ranking of the set of items in the reputation system based on a closeness of reputation scores for the items in the one or more dimensions to the one or more quantiles, and the one or more weights, wherein the closeness of the reputation scores to the one or more quantiles is based on a rectilinear distance between the reputation scores and the one or more quantiles; and

providing the ranking of the set of items in a response to the query.

2. The computer-implemented method of claim 1, wherein obtaining the query comprising the one or more dimensions and the one or more weights comprises:

obtaining a dimension from the query; and

identifying a weight associated with the dimension based on a querying pattern associated with the query.

3. The computer-implemented method of claim 1, wherein obtaining the ranking of the items in the reputation system based on the reputation scores for the items comprises:

obtaining the set of items in the reputation system with the reputation scores in the one or more dimensions; and

generating the ranking of the items in the one or more dimensions based on the reputation scores and the weights associated with the dimensions, wherein the weights are determined based on relative weighting or importance of the dimensions specified in the query.

4. The computer-implemented method of claim 1, wherein obtaining the query comprising the one or more dimensions and the one or more weights further comprises:

extracting, from the query, one or more quantiles associated with the dimensions; and

upon detecting an absence of the quantile from the query, associating a default quantile with the dimension.

5. The computer-implemented method of claim 4, wherein obtaining the ranking of the items in the reputation system based on the reputation scores comprises:

generating the ranking according to a closeness of a subset of the reputation scores for each of the items to the one or more quantiles.

6. The computer-implemented method of claim 5, wherein the closeness of the subset of the reputations scores to the one or more quantiles is based on a rectilinear distance between the subset of the reputation scores and the one or more quantiles.

7. The computer-implemented method of claim 1, wherein the set of items is obtained using an inverted index of the one or more dimensions.

8. The computer-implemented method of claim 7, wherein the inverted index comprises pre-computed quantiles associated with the reputation scores.

9. The computer-implemented method of claim 1, wherein the reputation scores comprise an explicit reputation score and an inferred reputation score.

10. A reputation system, comprising:

a ranking apparatus comprising at least a processor, configured to;

obtain a set of reputation scores in one or more dimensions for a set of items in the reputation system, wherein the dimensions comprise skills and the items comprise users; and

obtain a ranking of the set of items based on a closeness of the reputation scores to one or more quantiles associated with the one or more dimensions, and one or more weights associated with the one or more dimensions, wherein the closeness of the reputation scores to the one or more quantiles is based on a rectilinear distance between the reputation scores and the one or more quantiles, and wherein the quantiles specify skill levels desired for the users, and wherein the weights specify importance of the skills; and

a query-processing apparatus comprising at least a processor, configured to;

obtain a query comprising the one or more dimensions and the one or more weights associated with the one or more dimensions, wherein the query further comprises the one or more quantiles associated with the one or more dimensions; and

provide the ranking of the set of items in a response to the query.

11. The reputation system of claim 10, wherein obtaining the query comprising the one or more dimensions and the one or more weights comprises:

obtaining a dimension from the query; and

identifying a weight associated with the dimension based on a querying pattern associated with the query.

12. The reputation system of claim 10, wherein obtaining the ranking of the items in the reputation system based on the reputation scores for the items comprises:

obtaining the set of items in the reputation system with the reputation scores in the one or more dimensions; and

generating the ranking of the items in the one or more dimensions based on the reputations scores and the weights associated with the dimensions, wherein the weights are determined based on relative weighting or importance of the dimensions specified in the query.

13. The reputation system of claim 10, wherein obtaining the query comprising the one or more dimensions and the one or more weights comprises:

extracting, from the query, one or more quantiles associated with the dimensions; and

upon detecting an absence of the quantile from the query, associating a default quantile with the dimension.

14. The reputation system of claim 13, wherein obtaining the ranking of the items in the reputation system based on the reputation scores comprises:

generating the ranking according to a closeness of a subset of the reputation scores for each of the items to the one or more quantiles.

15. A non-transitory computer-readable storage medium storing instructions that, when executed by a computer, cause the computer to perform a method for querying a reputation system to rank a set of items, the method comprising:

obtaining a query specifying one or more dimensions and one or more weights associated with the one or more dimensions, wherein the query further comprises one or more quantiles associated with the one or more dimensions, wherein the dimensions comprise skills and the items comprise users, wherein the quantiles specify skill levels desired for the users, and wherein the weights specify importance of the skills;

obtaining a ranking of the set of the items based on a closeness of reputation scores for the items in the one or more dimensions to the one or more quantiles, and the one or more weights, wherein the closeness of the reputation scores to the one or more quantiles is based on a rectilinear distance between the reputation scores and the one or more quantiles; and

providing the ranking of the set of items in a response to the query.

16. The non-transitory computer-readable storage medium of claim 15, wherein obtaining the query specifying the one or more dimensions and the one or more associated weights comprises:

obtaining a dimension from the query; and

identifying a weight associated with the dimension based on a querying pattern associated with the query.

17. The non-transitory computer-readable storage medium of claim 15, wherein obtaining the ranking of the items based on the reputation scores for the items comprises:

obtaining the set of items in the reputation system with the reputation scores in the one or more dimensions; and

generating the ranking of the items in the one or more dimensions based on the reputation scores and the weights associated with the dimensions, wherein the weights are determined based on relative weighting or importance of the dimensions specified in the query.

18. The non-transitory computer-readable storage medium of claim 15, wherein obtaining the query comprising the one or more dimensions and the one or more weights comprises:

extracting, from the query, one or more quantiles associated with the dimensions; and

upon detecting an absence of the quantile from the query, associating a default quantile with the dimension.

19. The non-transitory computer-readable storage medium of claim 18, wherein obtaining the ranking of the items in the reputation system based on the reputation scores comprises:

generating the ranking according to a closeness of a subset of the reputation scores for each of the items to the one or more quantiles.