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Replacing the irreplaceable: Fast algorithms for team member recommendation

Li, L and Tong, H and Cao, N and Ehrlich, K and Lin, YR and Buchler, N (2015) Replacing the irreplaceable: Fast algorithms for team member recommendation. In: UNSPECIFIED.

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In this paper, we study the problem of Team Member Replacement - given a team of people embedded in a social network working on the same task, find a good candidate to best replace a team member who becomes unavailable to perform the task for certain reason (e.g., conflicts of interests or resource capacity). Prior studies in teamwork have suggested that a good team member replacement should bring synergy to the team in terms of having both skill matching and structure matching. However, existing techniques either do not cover both aspects or consider the two aspects independently. In this work, we propose a novel problem formulation using the concept of graph kernels that takes into account the interaction of both skill and structure matching requirements. To tackle the computational challenges, we propose a family of fast algorithms by (a) designing effective pruning strategies, and (b) exploring the smoothness between the existing and the new team structures. We conduct extensive experimental evaluations and user studies on real world datasets to demonstrate the effectiveness and efficiency. Our algorithms (a) perform significantly better than the alternative choices in terms of both precision and recall and (b) scale sub-linearly.


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Item Type: Conference or Workshop Item (UNSPECIFIED)
Status: Published
CreatorsEmailPitt UsernameORCID
Li, L
Tong, H
Cao, N
Ehrlich, K
Lin, YRYURULIN@pitt.eduYURULIN0000-0002-8497-3015
Buchler, N
Date: 18 May 2015
Date Type: Publication
Journal or Publication Title: WWW 2015 - Proceedings of the 24th International Conference on World Wide Web
Page Range: 636 - 646
DOI or Unique Handle: 10.1145/2736277.2741132
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
Date Deposited: 26 Jun 2015 18:52
Last Modified: 02 Jul 2019 12:55


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