Abstract

Crowd sourcing is emerging as a powerful paradigm to solve a wide range of tedious and complex problems in various enterprise applications. It spawns the issue of finding the unknown collaborative and competitive group of solvers. The formation of collaborative team should provide the best solution and treat that solution as a trade secret avoiding data leak between competitive teams due to reward behind the outsourcing of the issue. The formation of effective competitive teams not only requires adequate skills between members of each team, but also good team connectivity through social network and to provide the best solution and treat that solution as a trade secret avoiding data leak between teams due to reward behind the outsourcing of the issue. In this paper, we propose a data leak aware crowd sourcing system called Social Crowd. We introduce a clustering algorithm that uses social relationships between crowd workers to discover all possible teams while avoiding inter-team data leakage.

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