ABSTRACT
We introduce TeamGen, an interactive team formation system, to form project teams interactively by leveraging professional social network information of potential members. Unlike earlier approaches that focused on creating flat teams, i.e., teams without communities and central authorities, we model teams as hierarchical structures to reflect the ubiquitous nature of teams in real commercial and open source projects. Correspondingly, our team formation algorithms emphasize local density of sub teams to assess communication costs of newly formed teams. During the demonstration, audience can (a) explore professional social network of potential members, (b) learn the effectiveness and efficiency of our proposed team formation algorithms by comparing them with existing ones, (c) inspect and understand the process of team formation, and (d) interactively refine a project team by revoking computed position assignments.
- A. An, M. Kargar, and M. ZiHayat. Finding affordable and collaborative teams from a network of experts. In Proceedings of the 13th SIAM International Conference on Data Mining, May 2-4, 2013. Austin, Texas, USA., pages 587--595, 2013.Google Scholar
- A. Anagnostopoulos, L. Becchetti, C. Castillo, A. Gionis, and S. Leonardi. Power in unity: forming teams in large-scale community systems. In Proceedings of the 19th ACM Conference on Information and Knowledge Management, CIKM 2010, Toronto, Ontario, Canada, October 26-30, 2010, pages 599--608, 2010. Google ScholarDigital Library
- C. C. Cao, J. She, Y. Tong, and L. Chen. Whom to ask? jury selection for decision making tasks on micro-blog services. CoRR, abs/1208.0273, 2012. Google ScholarDigital Library
- C. Ding, F. Xia, G. Gopalakrishnan, W. Qian, and A. Zhou. Online formation of large tree-structured team. In Database Systems for Advanced Applications - DASFAA 2017 International Workshops: BDMS, BDQM, MoI, and SeCoP, Suzhou, Jiangsu, China, March 27-30, 2017, Proceedings, 2017.Google ScholarCross Ref
- M. Kargar and A. An. Discovering top-k teams of experts with/without a leader in social networks. In Proceedings of the 20th ACM Conference on Information and Knowledge Management, CIKM 2011, Glasgow, United Kingdom, October 24-28, 2011, pages 985--994, 2011. Google ScholarDigital Library
- M. Kargar, A. An, and M. ZiHayat. Efficient bi-objective team formation in social networks. In Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2012, Bristol, UK, September 24--28, 2012. Proceedings, Part II, pages 483--498, 2012.Google ScholarCross Ref
- T. Lappas, K. Liu, and E. Terzi. Finding a team of experts in social networks. In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28 - July 1, 2009, pages 467--476, 2009. Google ScholarDigital Library
- A. Majumder, S. Datta, and K. V. M. Naidu. Capacitated team formation problem on social networks. In The 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '12, Beijing, China, August 12-16, 2012, pages 1005--1013, 2012. Google ScholarDigital Library
- S. S. Rangapuram, T. Bühler, and M. Hein. Towards realistic team formation in social networks based on densest subgraphs. In 22nd International World Wide Web Conference, WWW '13, Rio de Janeiro, Brazil, May 13-17, 2013, pages 1077--1088, 2013. Google ScholarDigital Library
Index Terms
- TeamGen: An Interactive Team Formation System Based on Professional Social Network
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