1 research outputs found
Incentivizing the Workers for Truth Discovery in Crowdsourcing with Copiers
Crowdsourcing has become an efficient paradigm for performing large scale
tasks. Truth discovery and incentive mechanism are fundamentally important for
the crowdsourcing system. Many truth discovery methods and incentive mechanisms
for crowdsourcing have been proposed. However, most of them cannot be applied
to deal with the crowdsourcing with copiers. To address the issue, we formulate
the problem of maximizing the social welfare such that all tasks can be
completed with the least confidence for truth discovery. We design an incentive
mechanism consisting truth discovery stage and reverse auction stage. In truth
discovery stage, we estimate the truth for each task based on both the
dependence and accuracy of workers. In reverse auction stage, we design a
greedy algorithm to select the winners and determine the payment. Through both
rigorous theoretical analysis and extensive simulations, we demonstrate that
the proposed mechanisms achieve computational efficiency, individual
rationality, truthfulness, and guaranteed approximation. Moreover, our truth
discovery method shows prominent advantage in terms of precision when there are
copiers in the crowdsourcing systems.Comment: 12 pages, 8 figure