By Topic

Leveraging social networks for corporate staffing and expert recommendation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

6 Author(s)
Chenthamarakshan, V. ; IBM India Research Laboratories, Embassy Golf Links Business Park, Inner Ring Road, Bangalore 560071, India ; Dey, K. ; Hu, J. ; Mojsilovic, A.
more authors

Effective management of human resources is a significant challenge faced by most organizations. In this paper, we look at two problems that arise in large, globally distributed organizations: staffing projects with the required subject matter experts and connecting subject matter experts to other employees who can benefit from their expertise. Several approaches based on automated skill matching have been suggested in the past to solve these problems. However, we argue that social relationships play an important role in both of these functions, and better matches can be obtained by combining skill matching with rich social interaction data. We describe two systems that exploit social networking data to solve these problems and report the results of real life experiments performed using these systems.

Note: The Institute of Electrical and Electronics Engineers, Incorporated is distributing this Article with permission of the International Business Machines Corporation (IBM) who is the exclusive owner. The recipient of this Article may not assign, sublicense, lease, rent or otherwise transfer, reproduce, prepare derivative works, publicly display or perform, or distribute the Article.  

Published in:

IBM Journal of Research and Development  (Volume:53 ,  Issue: 6 )