Time constraint-based team formation in social networks

We investigate the problem of discovering a team of experts from a social network. Given a task with the skill set and the time span length, our goal is to obtain a team that covers all the skills, and have a low communication cost. Furthermore, each member of the team must have common free time whose length is no less than the span length required by the task. Previous works only attempt to cover the required skills and minimize the communication cost without taking the common free time of the individuals into account. We are the first to consider time factor in team formation and thus propose a novel team formation formulation with time constraint. We show that the problem is NP-hard. We first extend the RarestFirst algorithm to deal with our new problem, then propose two novel pruning strategies, called time pruning and skill pruning respectively, and an efficient algorithm called TSP-TF, to efficiently obtain an effective team for a given task. Experimental results show that TSP-TF outperforms the generalized RarestFirst algorithm by more than an order of magnitude.