  In order to accomplish complex tasks, it is often necessary to compose a team
consisting of experts with diverse competencies. However, for proper
functioning, it is also preferable that a team be socially cohesive. A team
recommendation system, which facilitates the search for potential team members
can be of great help both for (i) individuals who need to seek out
collaborators and (ii) managers who need to build a team for some specific
tasks.
  A decision support system which readily helps summarize such metrics, and
possibly rank the teams in a personalized manner according to the end users'
preferences, can be a great tool to navigate what would otherwise be an
information avalanche.
  In this work we present a general framework of how to compose such subsystems
together to build a composite team recommendation system, and instantiate it
for a case study of academic teams.
