Template-Driven Team Formation

Spiros Apostolou, Panayiotis Tsaparas, Evimaria Terzi

Abstract: The team-formation problem on social networks asks for a team of individuals that collectively possess the skills to perform a task and have low communication cost, as measured by their distances in the social network. Most related work assumes a flat structure in the team, where team members are all indistinguishable. However, in practice, teams often have complex structures and deep hierarchies, and members with distinct roles in these structures. In this paper, we consider the Template-Driven Team Formation problem, where given a fixed template structure for the team, in the form of a graph, and a designated role for each node in the template, we ask for workers that can fill the roles in the template, while minimizing the communication cost along the template edges. Although the problem is in general NP-hard, there are variants of the problem that can be solved optimally using dynamic programming. For the general case, we provide approximation and heuristic polynomial-time algorithms. We experiment on real data and we demonstrate that our heuristic algorithms perform well in practice while being significantly more efficient. Our case studies highlight the quality of the teams produced by our algorithms.