The Zen of Multidisciplinary Team Recommendation
This work addresses the need for individuals and managers to efficiently form effective teams, but it appears incremental as it builds on existing team recommendation concepts.
The paper tackles the problem of recommending multidisciplinary teams by proposing a general framework that integrates diverse competencies and social cohesion, and demonstrates it with a case study on academic teams.
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.