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

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.