CUSTOMIZING A USER-EXPERIENCE BASED ON A JOB-SEEKER SCORE

• US 20140143165A1
• Filed: 11/21/2012
• Published: 05/22/2014
• Est. Priority Date: 11/20/2012
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Posse, Christian, Hill, Andrew P., Rodriguez, Mario Sergio
• Application Number:
  US13/684,013
• Publication Number:
  US 20140143165A1
• Time in Patent Office: Days
• US Class Current: 705/319
• CPC Class Codes: G06Q 10/1053 Employment or hiring
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

Techniques are described herein for deriving, for each member of a social network service, a metric representing the job-seeking propensity of the member. Additionally, techniques for classifying each member with a job-seeking status (e.g., active job-seeker, passive job-seeker, or non-job-seeker) are described. A score-generating algorithm will analyze a variety of input data—including member profile data, social graph data, and activity or behavior data—to derive a job-seeker score, representing the job-seeking propensity of a member. Once derived, the metric is used to customize, personalize or otherwise tailor a user-experience.

Claims

1. A method comprising:

receiving a request to present one or more member profiles of members of a social network service;

responsive to the request, identifying a set of member profiles satisfying search criteria specified as part of the request;

with a processor-based ranking module, generating a ranking score for each member profile in the identified set of member profiles, the ranking score based in part on a job-seeker score or job-seeker classification associated with each respective member profile in the identified set of member profiles, the job-seeker score or job-seeker classification representing the likelihood that a respective member of the social network service is open to a change in employment position; and

causing a portion of the set of member profiles to be presented in a user interface in order of the ranking score generated for each respective member profile.

2. The method of claim 1, wherein the request is invoked to present to a recruiter a set of member profiles having member profile attributes satisfying a job listing that has been posted to a job listing service associated with the social network service.

3. The method of claim 1, wherein the request is invoked as a result of a user specifying the search criteria.

4. The method of claim 3, wherein the search criteria includes a job-seeker classification status including any one of:

active job-seeker, passive job-seeker, non-job-seeker.

5. The method of claim 1, wherein a job-seeker score or job-seeker classification associated with a particular member profile is derived by identifying lengths of time members having certain sets of member profile attributes remain in particular employment positions, and then identifying the length of time that a specific set of members having member profile attributes similar to the particular member remain in an employment position similar to the current employment position of the particular member.

6. The method of claim 5, further comprising:

using a machine learning algorithm to identify the lengths of time members having certain sets of member profile attributes remain in particular employment positions.

7. The method of claim 1, wherein a job-seeker score or job-seeker classification for a particular member is based in part on any one or more of the following member profile attributes specified in the member profile of a member:

an industry in which the member is employed, seniority of the member, tenure of the member at current position, gender of the member, or, proximity in time to a particular starting date anniversary.

8. The method of claim 1, wherein a job-seeker score or job-seeker classification for a particular member is based in part on analysis of member activity data for the member, the member activity data relating to various member interactions detected over a particular duration of time by the member with applications, services and/or content.

9. The method of claim 8, wherein the member activity data includes information specifying:

the number of times the member viewed results of a job search;

the number of times the member viewed results of a job recommendation engine;

the number of job applications submitted for job listings; and

, the number of times the member replied to a career-opportunity-related message received from another member.

10. The method of claim 1, wherein a job-seeker score or job-seeker classification for a particular member is based in part on analysis of member profile data of other members of the social network service who are either directly connected with the member, or share membership or association with an entity in common with the member, as indicated in a social graph maintained by the social network service.

11. The method of claim 1, wherein a job-seeker score or job-seeker classification of a particular member is based in part on analysis of member activity data of other members who are directly connected with the particular member, or other members who share membership or association with a particular entity in common with the particular member, as indicated in a social graph maintained by the social network service.

12. A system comprising:

a processor-based recommendation engine to i) identify a set of member profiles satisfying search criteria specified as part of a request, ii) generate a ranking score for each member profile in the identified set of member profiles, the ranking score based in part on a job-seeker score or job-seeker classification associated with each respective member profile in the identified set of member profiles, the job-seeker score or job-seeker classification representing the likelihood that a respective member of the social network service is open to a change in employment position, and ii) cause a portion of the set of member profiles to be presented in a user interface in order of the ranking score generated for each respective member profile.

13. A non-transitory computer readable storage medium storing instructions thereon, which, when executed by one or more processors of one or more computers, cause the one or more computers to:

identify a set of member profiles satisfying search criteria specified as part of a request;

generate a ranking score for each member profile in the identified set of member profiles, the ranking score based in part on a job-seeker score or job-seeker classification associated with each respective member profile in the identified set of member profiles, the job-seeker score or job-seeker classification representing the likelihood that a respective member of the social network service is open to a change in employment position; and

cause a portion of the set of member profiles to be presented in a user interface in order of the ranking score generated for each respective member profile.

14. A method comprising:

receiving a request to present content, the request associated with a member identifier of a member of a social network service;

determining a job-seeker score or job-seeker classification for the member; and

selecting content for presentation based on the determined job-seeker score or job-seeker classification of the member.

15. The method of claim 14, wherein the job-seeker score or job-seeker classification of the member represents the likelihood that the member is open to a change in employment positions.

16. The method of claim 14, wherein selecting content for presentation based on the determined job-seeker score or job-seeker classification of the member includes selecting a content module associated with a job recommendation application when the job-seeker score of the member is determined to be within some pre-defined range, or, when the job-seeker classification indicates the member has an active job-seeker status, the content module associated with the job recommendation engine including one or more job listings selected based on a determination that the one or more job listings are likely to be of interest to the member, the method further comprising:

causing the selected content to be presented.

17. The method of claim 14, wherein selecting content for presentation based on the determined job-seeker score or job-seeker classification of the member includes selecting content associated with a job recommendation application for presentation in a personalized activity stream of the member when the job-seeker score of the member is determined to be within some pre-defined range, or, when the job-seeker classification indicates the member has an active job-seeker status, the method further comprising:

causing the selected content to be presented in the personalized activity stream of the member.

18. The method of claim 14, wherein selecting content for presentation based on the determined job-seeker score or job-seeker classification of the member includes selecting content associated with a job recommendation application for presentation in an email to be communicated to the member when the job-seeker score of the member is determined to be within some pre-defined range, or, when the job-seeker classification indicates the member has an active job-seeker status, the method further comprising:

causing the selected content to be presented in an email communicated to the member.

19. The method of claim 14, wherein the job-seeker score or job-seeker classification of the member is derived by identifying lengths of time other members having certain sets of member profile attributes remain in particular employment positions, and then identifying the length of time that a specific set of members having member profile attributes similar to the particular member remain in an employment position similar to the current employment position of the member.

20. The method of claim 19, further comprising:

using a machine learning algorithm to identify the lengths of time members having certain sets of member profile attributes remain in particular employment positions.

21. The method of claim 14, wherein the job-seeker score or job-seeker classification of the member is determined based in part on any one or more of the following member profile attributes specified in the member profile of the member:

an industry in which the member is employed, seniority of the member, tenure of the member at current position, gender of the member, or, proximity in time to a particular starting date anniversary.

22. The method of claim 14, wherein the job-seeker score or job-seeker classification of the member is determined based in part on analysis of member activity data for the member, the member activity data relating to various member interactions detected over a particular duration of time by the member with applications, services and/or content.

23. The method of claim 22, wherein the member activity data includes information specifying:

the number of times the member viewed results of a job search;

the number of times the member viewed results of a job recommendation engine;

the number of job applications submitted for job listings; and

, the number of times the member replied to a career-opportunity-related message received from another member.

24. The method of claim 14, wherein the job-seeker score or job-seeker classification of the member is determined based in part on analysis of member profile data of other members of the social network service who are either directly connected with the member, or share membership or association with an entity in common with the member, as indicated in a social graph maintained by the social network service.

25. The method of claim 24, wherein the job-seeker score or job-seeker classification of the member is determined based in part on analysis of member activity data of other members who are directly connected with the particular member, or other members who share membership or association with a particular entity in common with the member, as indicated in a social graph maintained by the social network service.