NDLI: Replacing the Irreplaceable: Fast Algorithms for Team Member Recommendation

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Replacing the Irreplaceable: Fast Algorithms for Team Member Recommendation

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Replacing the Irreplaceable: Fast Algorithms for Team Member Recommendation

Content Provider	ACM Digital Library
Author	Tong, Hanghang Buchler, Norbou Li, Liangyue Ehrlich, Kate Cao, Nan Lin, Yu-Ru
Abstract	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.
Starting Page	636
Ending Page	646
Page Count	11
File Format	PDF
ISBN	9781450334693
DOI	10.1145/2736277.2741132
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-05-18
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Graph kernel Scalability Team member replacement
Content Type	Text
Resource Type	Article

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