The zen of multidisciplinary team recommendation

It is often necessary to compose a team consisting of experts with diverse competencies to accomplish complex tasks. However, for its 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 (a) individuals who need to seek out collaborators and for (b) managers who need to build a team for some specific tasks. Such a decision support system that readily helps summarize multiple metrics indicating a team (and its members) quality, and possibly rank the teams in a personalized manner according to the end users' preferences, thus serves as a tool to cope with what would otherwise be an information avalanche. In this work, we present Social Web Application for Team Recommendation, a general-purpose framework to compose various information retrieval and social graph mining and visualization subsystems together to build a composite team recommendation system, and instantiate it for a case study of academic teams.