METHODS AND SYSTEMS FOR RECOMMENDING EMPLOYEES FOR A TASK

• US 20150025928A1
• Filed: 07/17/2013
• Published: 01/22/2015
• Est. Priority Date: 07/17/2013
• Status: Abandoned Application

• Current Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Original Assignee: Xerox Corporation (Xerox Holdings Corp.)
• Inventors: Sun, Tong, Kang, Dhanwant S., Liu, Hua
• Application Number:
  US13/944,035
• Publication Number:
  US 20150025928A1
• Time in Patent Office: Days
• US Class Current: 705/7.14
• CPC Class Codes: G06Q 10/063112 Skill-based matching of a person or a group to a task

Abstract

A method, a system, and a computer program product for recommending one or more employees from a group of employees for a task are provided. For an employee in the group of employees a processor is used for determining a degree of separation metric with respect to other employees in the group of employees. Further, for the employee the processor is used for determining a personality metric based at least partially on a measure of past collaboration with other employees in the group of employees. The processor is further used for recommending the one or more employees from the group of employees for the task based on the degree of separation metric and the personality metric.

Claims

1. A method implemented on a computing device for recommending one or more employees from a group of employees for a task, the method comprising:

for an employee in the group of employees;

using a processor for

determining a degree of separation metric with respect to other employees in the group of employees; and

determining a personality metric based at least partially on a measure of past collaboration with other employees in the group of employees; and

using the processor for recommending the one or more employees from the group of employees for the task based on the degree of separation metric and the personality metric.

2. The method of claim 1, wherein the processor is further used for identifying one or more skills associated with each employee in the group of employees.

3. The method of claim 2, wherein the processor is further used for ranking each employee in the group of employees based at least in part on the one or more skills.

4. The method of claim 2, wherein the one or more skills comprises at least one of personal information, educational details, or employment history.

5. The method of claim 2, wherein the processor is further used for determining expertise of each employee in the group of employees for each skill of the one or more skills associated with the each employee.

6. The method of claim 1, wherein the degree of separation metric is based at least partially on a determined amount of professional closeness between the employee and other employees in the group of employees.

7. The method of claim 1, wherein the degree of separation is determined based on at least one of co-authorship, team membership, and organizational unit.

8. The method of claim 1, wherein the processor is further used for categorizing each employee in the group of employees in at least one of an individual category, an team player category, and an external collaborator category.

9. The method of claim 8, wherein the categorization of the employee in the individual category is based on a number of publications of the employee as an individual.

10. The method of claim 8, wherein the categorization of the employee in the team player category is based on a number of publications of the employee with other employees in the group of employees.

11. The method of claim 8, wherein the categorization of the employee in the external collaborator category is based on a number of publications of the employee with employees outside the group of employees.

12. The method of claim 1, wherein the processor is further used for specifying allocation constraints for the employee from the group of employees at a time, wherein the allocation constraints corresponds to a maximum number of teams to which the employee can be allocated.

13. A system for recommending one or more employees from a group of employees for a task, the system comprising:

a processor; and

a memory comprising;

a closeness determination module configured to determine a degree of separation metric for an employee from the group of employees with respect to other employees in the group of employees;

a personality module configured to determine a personality metric of the employee based at least partially on a measure of past collaboration of the employee with the other employees; and

a recommendation module configured to recommend one or more employees from the group of employees for the task based on at least one the degree of separation metric, or the personality metric, and

wherein the processor is operable to execute the closeness determination module, the personality module, and the recommendation module.

14. The system of claim 13 further comprising a skill extraction module configured to identify one or more skills associated with each employee the group of employees, wherein the processor executes the skill extraction module.

15. The system of claim 14, wherein the skill extraction module is further configured to ranking each employee in the group of employees based at least in part on the one or more skills.

16. The system of claim 13 further comprising a database for storing one or more skills associated with each employee in the group of employees.

17. The system of claim 13 further comprising a comparison module configured to determine a gap between the one or more skills of the employee with the one or more skills of other employees in the group of employees.

18. The system of claim 13, wherein the degree of separation metric is based at least partially on a determined amount of professional closeness between the employee and other employees in the group of employees.

19. The system of claim 13, wherein the personality module is further configured to categorize each employee in the group of employees in at least one of an individual category, a team player category, and an external collaborator category.

20. A computer program product for use with a computer, the computer program product comprising a computer-usable data carrier storing a computer readable program code embodied therein for recommending one or more employees from a group of employees for a task, the computer readable program code comprising:

program instruction means for identifying one or more skills associated with each employee in the group of employees;

program instruction means for ranking each employee in the group of employees based at least in part on the one or more skills;

program instruction means for determining a degree of separation metric for an employee from the group of employees with respect to other employees from the group of employees;

program instruction means for determining a personality metric of the employee based at least partially on a measure of past collaboration of the employee with the other employees; and

program instruction means for recommending one or more employees from the group of employees for the task based on at least one the degree of separation metric, or the personality metric.