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Graph Pattern Matching for Dynamic Team Formation

Shuai Ma,Jia Li,Chunming Hu,Xudong Liu,J. Huai

Published 2018 in arXiv.org

ABSTRACT

Finding a list of k teams of experts, referred to as top-k team formation, with the required skills and high collaboration compatibility has been extensively studied. However, existing methods have not considered the specific collaboration relationships among different team members, i.e., structural constraints, which are typically needed in practice. In this study, we first propose a novel graph pattern matching approach for top-k team formation, which incorporates both structural constraints and capacity bounds. Second, we formulate and study the dynamic top-k team formation problem due to the growing need of a dynamic environment. Third, we develop an unified incremental approach, together with an optimization technique, to handle continuous pattern and data updates, separately and simultaneously, which has not been explored before. Finally, using real-life and synthetic data, we conduct an extensive experimental study to show the effectiveness and efficiency of our graph pattern matching approach for (dynamic) top-k team formation.

PUBLICATION RECORD

  • Publication year

    2018

  • Venue

    arXiv.org

  • Publication date

    2018-01-03

  • Fields of study

    Computer Science

  • Identifiers
    arXiv 1801.01012
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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