Identification of Job Skill Sets and Targeted Advertising Based on Missing Skill Sets

• US 20140324721A1
• Filed: 04/29/2013
• Published: 10/30/2014
• Est. Priority Date: 04/29/2013
• Status: Active Grant

• Current Assignee: Monster Worldwide Incorporated (Randstad NV)
• Original Assignee: Monster Worldwide Incorporated (Randstad NV)
• Inventors: Rennison, Earl F., Arasada, Praveen, Luo, Jun
• Granted Patent: US 10,878,381 B2
• Time in Patent Office: Days
• US Class Current: 705/321
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• CPC Class Codes: G06Q 10/105 Human resources
• CPC Class Codes: G06Q 10/1053 Employment or hiring
• CPC Class Codes: G06Q 10/1057 Benefits or employee welfare, e.g. insurance, holiday or retirement packages
• CPC Class Codes: G06Q 50/2057 Career enhancement or continuing education service

Abstract

Methods and systems are disclosed for determining gaps in a user'"'"'s resume regarding skills or titles for a job, and recommending educational courses to the user based on those gaps. The user'"'"'s resume is received and analyzed for the user'"'"'s current set of skills. Various searching methods are used to identify a set of job requisitions based on a user'"'"'s input query for a job. The user'"'"'s skills are compared with a set of required skills associated with the set of job requisitions. Educational courses are identified for the skills that are required for the set of job requisitions but are not present in the user'"'"'s set of skills. The educational courses presented to the user via the search engine. The user'"'"'s resume can also be ranked relative to other resumes for the skills or titles required for a job.

Claims

1. A computer-implemented method for identifying gaps in a resume, the method comprising:

storing in a computer system a skill knowledge base comprising a collection of skills;

storing in the computer system a requisition knowledge base comprising a collection of job requisitions, each job requisition associated with one or more skills in the skill knowledge base;

storing in the computer system a resume knowledge base comprising a collection of resumes, each resume associated with one or more skills in the skill knowledge base;

storing in the resume knowledge base a resume of a user received into the computer system, the resume associated with one or more skills in the skill knowledge base that match resume skills in the resume;

receiving an input query from the user;

identifying by a search of the requisition knowledge base, a set of job requisitions matching the input query;

assigning a first weight to each of the skills in the matching set of job requisitions based on a frequency of occurrence of the skill across the collection of job requisitions in the requisition knowledge base;

selecting, based on the first weight, skills in the matching set of job requisitions as required skills for the input query;

identifying by a search of the resume knowledge base using the required skills as an input, a set of implied required skills that are subsumed by the required skills and that are associated with resumes identified by the search of the resume knowledge base;

assigning a second weight to each of the implied required skills based on a frequency of occurrence of the implied required skills in the collection of resumes in the resume knowledge base;

computing a score for each of the implied required skills based on the first weights and the second weights;

selecting, based on the scores, a subset of the implied required skills;

comparing the resume skills of the user with the subset of implied required skills; and

identifying gap skills of the user that are skills present in the subset of implied required skills and absent from the resume skills of the user.

2. The method of claim 1, further comprising providing for display to the user the identified gap skills.

3. The method of claim 1, further comprising:

storing in the computer system a course knowledge base comprising a collection of educational courses, each educational course associated with one or more skills in the skill knowledge base;

searching the course knowledge base based on the gap skills to retrieve a set of educational courses matching the gap skills; and

providing for display to the user the set of educational courses retrieved.

4. The method of claim 3, further comprising conducting a reverse search of the course knowledge base using the resume of the user to evaluate each of the educational courses retrieved against the resume.

5. The method of claim 1, wherein assigning a first weight comprises multiplying a number of job requisitions in the matching set of job requisitions having a given skill by a log inverse frequency of the given skill in the collection of job requisitions in the requisition knowledge base.

6. The method of claim 5, wherein the log inverse frequency is calculated as a Term Frequency Inverse Document Frequency (TFIDF) calculation.

7. The method of claim 1, wherein selecting, based on the first weight, a plurality of the skills in the matching set of job requisitions as required skills comprises sorting the skills of the matching set of job requisition based on the first weights and selecting a specified number of the sorted skills as required skills.

8. The method of claim 1, wherein assigning a first weight comprises assigning a Jaccard score to determine which skills are most relevant to the matching set of job requisitions.

9. The method of claim 1, wherein assigning second weights to the implied required skills comprises determining a weight for each of the implied required skills based on a log frequency of the implied required skill in the resumes of the fourth knowledge base.

10. The method of claim 1, wherein computing a score for each of the implied required skills based on the first weights and the second weights comprises determining a weighted average for each of the second weights using the first weights.

11. The method of claim 10, wherein selecting, based on the scores, a subset of the implied required skills comprises sorting the implied required skills based on the weighted averages of the second weights and selecting a specified number of the sorted implied required skills as the subset of implied required skills.

12. The method of claim 1, wherein the matching set of job requisitions comprises a single job requisition.

13. The method of claim 12, wherein assigning first weights to the skills in the matching set of job requisitions comprises assigning a same weight to each of the skills of the single job requisition.

14. The method of claim 12, wherein assigning first weights to the skills in the matching set of job requisitions comprises assigning first weights by weighting each of the skills in the single job requisition based on a log inverse frequency of the skill in the collection of job requisitions of the requisition knowledge base.

15. A computer-implemented method for identifying gaps in a resume, the method comprising:

storing in a computer system a title knowledge base comprising a collection of titles;

storing in the computer system a requisition knowledge base comprising a collection of job requisitions, each job requisition associated with one or more titles in the title knowledge base;

storing in the computer system a resume knowledge base comprising a collection of resumes, each resume associated with one or more titles in the title knowledge base;

storing in the resume knowledge base a resume of a user received into the computer system, the resume associated with one or more titles in the title knowledge base that match resume titles in the resume;

receiving an input query from the user;

identifying by a search of the requisition knowledge base, a set of job requisitions matching the input query;

assigning a first weight to each of the titles in the matching set of job requisitions based on a frequency of occurrence of the title across the collection of job requisitions in the requisition knowledge base;

selecting, based on the first weight, titles in the matching set of job requisitions as required titles for the input query;

identifying by a search of the resume knowledge base using the required titles as an input, a set of implied required titles that are subsumed by the required titles and that are associated with resumes identified by the search of the resume knowledge base;

assigning a second weight to each of the implied required titles based on a frequency of occurrence of the implied required titles in the collection of resumes in the resume knowledge base;

computing a score for each of the implied required titles based on the first weights and the second weights;

selecting, based on the scores, a subset of the implied required titles;

comparing the resume titles of the user with the subset of implied required titles; and

identifying gap titles of the user that are titles present in the subset of implied required titles and absent from the resume titles of the user.

16. The method of claim 15, further comprising providing for display to the user the identified gap titles.

17. The method of claim 15, further comprising:

storing in the computer system a course knowledge base comprising a collection of educational courses, each educational course associated with one or more titles in the title knowledge base;

searching the course knowledge base based on the gap titles to retrieve a set of educational courses matching the gap titles; and

providing for display to the user the set of educational courses retrieved

18. The method of claim 15, further comprising conducting a reverse search of the course knowledge base using the resume of the user to evaluate each of the educational courses retrieved against the resume.

19. The method of claim 15, wherein assigning a first weight comprises multiplying a number of job requisitions in the matching set of job requisitions having a given title by a log inverse frequency of the given title in the collection of job requisitions in the requisition knowledge base.

20. The method of claim 19, wherein the log inverse frequency is calculated as a Term Frequency Inverse Document Frequency (TFIDF) calculation.

21. The method of claim 15, wherein selecting, based on the first weight, a plurality of the titles in the matching set of job requisitions as required titles comprises sorting the titles of the matching set of job requisition based on the first weights and selecting a specified number of the sorted titles as required titles.

22. The method of claim 15, wherein assigning a first weight comprises assigning a Jaccard score to determine which titles are most relevant to the matching set of job requisitions.

23. The method of claim 15, wherein assigning second weights to the implied required titles comprises determining a weight for each of the implied required titles based on a log frequency of the implied required title in the resumes of the fourth knowledge base.

24. The method of claim 15, wherein computing a score for each of the implied required titles based on the first weights and the second weights comprises determining a weighted average for each of the second weights using the first weights.

25. The method of claim 24, wherein selecting, based on the scores, a subset of the implied required titles comprises sorting the implied required titles based on the weighted averages of the second weights and selecting a specified number of the sorted implied required titles as the subset of implied required titles.

26. The method of claim 15, wherein the matching set of job requisitions comprises a single job requisition.

27. The method of claim 26, wherein assigning first weights to the titles in the matching set of job requisitions comprises assigning a same weight to each of the titles of the single job requisition.

28. The method of claim 26, wherein assigning first weights to the titles in the matching set of job requisitions comprises assigning first weights by weighting each of the titles in the single job requisition based on a log inverse frequency of the title in the collection of job requisitions of the requisition knowledge base.

29. A computer-implemented method for ranking a resume, the method comprising:

storing in a computer system a skill knowledge base comprising a collection of skills;

storing in the computer system a requisition knowledge base comprising a collection of job requisitions, each job requisition associated with one or more skills in the skill knowledge base;

storing in the computer system a resume knowledge base comprising a collection of resumes, each resume associated with one or more skills in the skill knowledge base;

storing in the resume knowledge base a resume of a user received into the computer system, the resume associated with one or more skills in the skill knowledge base that match resume skills in the resume;

receiving an input query from the user;

identifying by a search of the requisition knowledge base a set of job requisitions matching the input query;

assigning a first weight to each of the skills in the matching set of job requisitions based on a frequency of occurrence of the skill across the collection of job requisitions in the requisition knowledge base;

selecting, based on the first weight, skills in the matching set of job requisitions as required skills for the input query;

identifying by a search of the resume knowledge base using the required skills as an input a set of implied required skills that are subsumed by the required skills and that are associated with resumes identified by the search of the resume knowledge base;

assigning a second weight to each of the implied required skills based on a frequency of occurrence of the implied required skills in the collection of resumes in the resume knowledge base;

computing a score for each of the implied required skills based on the first weights and the second weights;

selecting, based on the scores, a subset of the implied required skills;

scoring the resume of the user based on each of the implied required skills in the subset;

scoring the collection of resumes in the resume knowledge bases based on each of the implied required skills in the subset;

determining, based on the score of the user'"'"'s resume and the scores of the collection of resumes, a ranking for the resume of the user relative to a plurality of resumes in the resume knowledge base with regard to each of the implied required skills in the subset; and

providing for display to the user the ranking of the resume of the user.

30. The method of claim 29, wherein the ranking is a percentile rating of the resume of the user relative to the collection of resumes in the resume knowledge base.

31. The method of claim 29, further comprising determining a ranking of the resume of the user relative to the collection of resumes in the resume knowledge base for a type of job search conducted by the user.

32. A computer-implemented method for ranking a resume, the method comprising:

storing in a computer system a title knowledge base comprising a collection of titles;

storing in the computer system a requisition knowledge base comprising a collection of job requisitions, each job requisition associated with one or more titles in the title knowledge base;

storing in the computer system a resume knowledge base comprising a collection of resumes, each resume associated with one or more titles in the title knowledge base;

storing in the resume knowledge base a resume of a user received into the computer system, the resume associated with one or more titles in the title knowledge base that match resume titles in the resume;

receiving an input query from the user;

identifying by a search of the requisition knowledge base a set of job requisitions matching the input query;

assigning a first weight to each of the titles in the matching set of job requisitions based on a frequency of occurrence of the title across the collection of job requisitions in the requisition knowledge base;

selecting, based on the first weight, titles in the matching set of job requisitions as required titles for the input query;

identifying by a search of the resume knowledge base using the required titles as an input a set of implied required titles that are subsumed by the required titles and that are associated with resumes identified by the search of the resume knowledge base;

assigning a second weight to each of the implied required titles based on a frequency of occurrence of the implied required titles in the collection of resumes in the resume knowledge base;

computing a score for each of the implied required titles based on the first weights and the second weights;

selecting, based on the scores, a subset of the implied required titles;

scoring the resume of the user based on each of the implied required titles in the subset;

scoring the collection of resumes in the resume knowledge bases based on each of the implied required titles in the subset;

determining, based on the score of the user'"'"'s resume and the scores of the collection of resumes, a ranking for the resume of the user relative to a plurality of resumes in the resume knowledge base with regard to each of the implied required titles in the subset; and

providing for display to the user the ranking of the resume of the user.

33. The method of claim 32, wherein the ranking is a percentile rating of the resume of the user relative to the collection of resumes in the resume knowledge base.

34. The method of claim 32, further comprising determining a ranking of the resume of the user relative to the collection of resumes in the resume knowledge base for a type of job search conducted by the user.