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A Framework for Trust-Based Multidisciplinary Team Recommendation

  • Conference paper
User Modeling, Adaptation, and Personalization (UMAP 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7899))

Abstract

Often one needs to form teams in order to perform a complex collaborative task. Therefore, it is interesting and useful to assess how well constituents of a team have performed, and leverage this knowledge to guide future team formation. In this work we propose a model for assessing the reputation of participants in collaborative teams. The model takes into account several features such as the different skills that a participant has and the feedback of team participants on her/his previous works. We validate our model based on synthetic datasets extrapolated from real-life scenarios.

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Author information

Authors and Affiliations

  1. DiSTA, University of Insubria, Italy

    Lorenzo Bossi & Alberto Trombetta

  2. School of Computer Engineering, Nanyang Technological University, Singapore

    Stefano Braghin & Anwitaman Datta

Authors
  1. Lorenzo Bossi
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  2. Stefano Braghin
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  3. Anwitaman Datta
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  4. Alberto Trombetta
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Editor information

Editors and Affiliations

  1. Department of Computer and Information Science, University of Delaware, 19716, Delaware, DE, USA

    Sandra Carberry

  2. School of Computing, National College of Ireland, Mayor Street, IFSC, Dublin 1, Ireland

    Stephan Weibelzahl

  3. Dipartimento di Ingegneria, Roma Tre University, Via della Vasca Navale, 79, 00146, Rome, Italy

    Alessandro Micarelli

  4. Department of Computer Science, University of Bari Aldo Moro, 70126, Bari, Italy

    Giovanni Semeraro

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© 2013 Springer-Verlag Berlin Heidelberg

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Bossi, L., Braghin, S., Datta, A., Trombetta, A. (2013). A Framework for Trust-Based Multidisciplinary Team Recommendation. In: Carberry, S., Weibelzahl, S., Micarelli, A., Semeraro, G. (eds) User Modeling, Adaptation, and Personalization. UMAP 2013. Lecture Notes in Computer Science, vol 7899. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38844-6_4

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  • DOI: https://doi.org/10.1007/978-3-642-38844-6_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38843-9

  • Online ISBN: 978-3-642-38844-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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