SKILL RANKING SYSTEM

• US 20120197993A1
• Filed: 01/24/2012
• Published: 08/02/2012
• Est. Priority Date: 01/27/2011
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Linkedln Corporation
• Inventors: Skomoroch, Peter N., Gupta, Abhishek, Patil, Dhanurjay A.S., Hayes, Matthews T.
• Application Number:
  US13/357,302
• Publication Number:
  US 20120197993A1
• Time in Patent Office: Days
• US Class Current: 709/204
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: G06F 16/355 Class or cluster creation or modification
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 10/06398 Performance of employee with respect to a job function
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

In an example disclosed is a method of ranking social networking service member skills by retrieving from non-volatile storage a plurality of member profiles created by a plurality of members of a social networking service, running a text classification algorithm to determine which of the plurality of members possesses a skill that matches any of a plurality of provided skills and associated skill attributes; and for at least one skill of the plurality of provided skills, identifying the plurality of members that possess the skill and ranking the plurality of members relative to one another using a ranking algorithm, the ranking algorithm being based in part upon weighted interactions among the plurality of members that possess the given skill, the weighted interactions comprising endorsements between a first member who possesses the given skill and a second member who possesses the given skill.

Claims

1. A method comprising:

retrieving from non-volatile storage a plurality of member profiles created by a plurality of members of a social networking service;

executing, on one or more computer processors, a text classification algorithm to determine which of the plurality of members possesses a skill that matches any of a plurality of provided skills and associated skill attributes; and

for at least one skill of the plurality of provided skills, identifying the plurality of members that possess the skill and ranking the plurality of members relative to one another using a ranking algorithm, the ranking algorithm being based in part upon weighted interactions among the plurality of members that possess the given skill, the weighted interactions comprising endorsements between a first member who possesses the given skill and a second member who possesses the given skill.

2. The method of claim 1, wherein the associated skill attributes includes co-ocurrent phrases.

3. The method of claim 1, wherein the text classification algorithm is a bayes classifier.

4. The method of claim 3, wherein evidence used in the bayes classifier comprises the plurality of provided skills and associated skill attributes.

5. The method of claim 1, further comprising:

collecting a plurality of member behavior information.

6. The method of claim 5, wherein the weighted interactions include the plurality of member behavior information.

7. The method of claim 1, wherein the endorsements comprise:

an invitation to connect sent by the first member to the second member.

8. The method of claim 1, wherein the endorsements comprise:

member profile views of the first member by the second member.

9. The method of claim 1, wherein the endorsements comprise:

inclusion of the first member by the second member in the second member'"'"'s address book.

10. The method of claim 1, wherein the endorsements comprise:

the first and second members appearing in a common group on the social networking site.

11. The method of claim 1, further comprising:

calculating a score for a company for the given skill, by aggregating a rank for the given skill of any of the plurality of members who possess the given skill and who report in their profiles that they work for the company; and

based on the company score, increasing or decreasing the rank for the given skill of any of the plurality of members who possess the given skill and who report in their profiles that they work for the company.

12. The method of claim 1, further comprising:

adjusting a rank of a particular member selected from the plurality of members who possess the given skill based upon connections associated with the particular member on a second social networking site.

13. The method of claim 1, wherein a weight given to a particular weighted interaction between the plurality of members who possess the given skill is based upon a rank of the members involved in the interaction.

14. The method of claim 13 further comprising:

iteratively adjusting the weights and recalculating the rankings until convergence.

15. The method of claim 1, further comprising:

calculating a score for a geographic region for the given skill by aggregating a rank for the given skill of any of the plurality of members who possess the given skill and who report in their profiles that they work in the geographic area; and

based on the geographic score, increasing or decreasing the rank for the given skill of any of the plurality of members that possess the given skill and who report in their profiles that they work in the geographic region.

16. A system comprising:

a retrieval module executable on a computer processor to retrieve a plurality of member profiles created by a plurality of members of a social networking service;

a tagging module executable on one or more computer processors to run a text classification algorithm on the plurality of member profiles to determine which of the plurality of members possesses a skill that matches any of a plurality of provided skills and associated skill attributes; and

a ranking module configured to;

for at least one skill of the plurality of provided skills, identify the plurality of members that possess the skill and rank them relative to each other using a ranking algorithm, the ranking algorithm being based at least upon weighted interactions among members that posses the given skill, the weighted interactions comprising endorsements between a first member that possesses the given skill and a second member that possesses the given skill.

17. The system of claim 16, wherein the associated skill attributes includes co-occurrent phrases.

18. The system of claim 16, wherein the text classification algorithm is a bayes classifier.

19. The system of claim 18, wherein evidence used in the bayes classifier comprises the provided skills and associated skill attributes.

20. The system of claim 16, wherein the tagging module collects a plurality of member behavior metrics.

21. The system of claim 20, wherein the rankings module adjusts the ranking of the members that possess the skill based upon the plurality of member behavior metrics.

22. The system of claim 16, wherein the endorsements comprise:

an invitation to connect sent by the first member to the second member.

23. The system of claim 16, wherein the endorsements comprise:

member profile views of the first member by the second member.

24. The system of claim 16, wherein the endorsements comprise:

inclusion of the first member by the second member in the second member'"'"'s address book.

25. The system of claim 16, wherein the endorsements comprise:

the first and second members appearing in a common group on the social networking site.

26. The system of claim 16, wherein the ranking module calculates a score of a company for the given skill, by aggregating a rank for the given skill of any of the plurality of members who possess the given skill and who report in their profiles that they work for the company;

and

based on the company score, increasing or decreasing the rank for the given skill of any of the plurality of members that possess the given skill and who report in their profiles that they work for the company.

27. The system of claim 16, wherein the ranking module adjusts a rank of a particular member selected from the plurality of members that possess the given skill based upon the number of connections associated with the particular member on a second social networking site.

28. The system of claim 16, wherein the ranking module adjusts weights given to a particular weighted interaction between the plurality of members that possess the given skill based upon a rank of the members involved in the interaction.

29. The system of claim 28, wherein the ranking module iteratively adjusts the weights and recalculates until convergence.

30. The system of claim 16, wherein the ranking algorithm calculates a score of a geographic region for the given skill, by aggregating a rank for the given skill of any of the plurality of members who possess the given skill and who report in their profiles that they work in the geographic area;

and

based on the geographic score, increasing or decreasing the rank for the given skill of any of the plurality of members that possess the given skill and who report in their profiles that they work in the geographic region.

31. A machine-readable storage medium including instructions, which when executed on the machine, causes the machine to:

retrieve from non-volatile storage a plurality of member profiles created by a plurality of members of a social networking service;

execute, a text classification algorithm to determine which of the plurality of members possesses a skill that matches any of a plurality of provided skills and associated skill attributes; and

for at least one skill of the plurality of provided skills, identify the plurality of members that possess the skill and rank the plurality of members relative to one another using a ranking algorithm, the ranking algorithm being based in part upon weighted interactions among the plurality of members that possess the given skill, the weighted interactions comprising endorsements between a first member who possesses the given skill and a second member who possesses the given skill.