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Using Machine Learning to Predict Links and Improve Steiner Tree Solutions to Team Formation Problems

  • Peter KeaneEmail author
  • Faisal Ghaffar
  • David Malone
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 882)

Abstract

The team formation problem has existed for many years in various guises. One important problem in the team formation problem is to produce small teams that have a required set of skills. We propose a framework that incorporates machine learning to predict unobserved links between collaborators, alongside improved Steiner tree problems to form small teams to cover given tasks. Our framework not only considers size of the team but also how likely are team members are going to collaborate with each other. The results show that this model consistently returns smaller collaborative teams.

Keywords

Team formation Link prediction Steiner tree 

Notes

Acknowledgement

This publication has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) and is co-funded under the European Regional Development Fund under Grant Number 13/RC/2077.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Maynooth UniversityMaynoothIreland
  2. 2.Innovation Exchange, IBM IrelandDublinIreland

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