Team formation for generalized tasks in expertise social networks

Cheng-Te Li, Man Kwan Shan

研究成果: Conference contribution

99 引文 斯高帕斯(Scopus)

摘要

Given an expertise social network and a task consisting of a set of required skills, the team formation problem aims at finding a team of experts who not only satisfy the requirements of the given task but also communicate to one another in an effective manner. To solve this problem, Lappas et al. [9] has proposed the Enhance Steiner algorithm. In this work, we generalize this problem by associating each required skill with a specific number of experts. We propose three approaches to form an effective team for the generalized task. First, we extend the Enhanced-Steiner algorithm to a generalized version for generalized tasks. Second, we devise a density-based measure to improve the effectiveness of the team. Third, we present a novel grouping-based method that condenses the expertise information to a group graph according to required skills. This group graph not only drastically reduces the search space but also avoid redundant communication costs and irrelevant individuals when compiling team members. Experimental results on the DBLP dataset show the teams found by our methods performs well in both effectiveness and efficiency.

原文English
主出版物標題Proceedings - SocialCom 2010
主出版物子標題2nd IEEE International Conference on Social Computing, PASSAT 2010: 2nd IEEE International Conference on Privacy, Security, Risk and Trust
頁面9-16
頁數8
DOIs
出版狀態Published - 2010
事件2nd IEEE International Conference on Social Computing, SocialCom 2010, 2nd IEEE International Conference on Privacy, Security, Risk and Trust, PASSAT 2010 - Minneapolis, MN, United States
持續時間: 2010 八月 202010 八月 22

Other

Other2nd IEEE International Conference on Social Computing, SocialCom 2010, 2nd IEEE International Conference on Privacy, Security, Risk and Trust, PASSAT 2010
國家/地區United States
城市Minneapolis, MN
期間10-08-2010-08-22

All Science Journal Classification (ASJC) codes

  • 電腦網路與通信
  • 電腦科學應用
  • 資訊系統

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