Abstract: Task allocation mechanism plays an important role on crowdsourcing task quality. However, the existing allocation methods do not consider the bilateral user preferences of crowdsourcing, the accuracy of the allocation results remains to be improved, and there are many crowdsourcing users who are not satisfied with the current allocated crowdsourcing tasks, causing the phenomenon of low quality of crowdsourcing task accomplishment. Therefore a crowdsourcing task allocation method based on preference matching is proposed. Firstly, this method compute satisfaction and construct satisfaction matrix by using the preference of crowdsourcing tasks and workers. Secondly, by referring to the idea of stable matching and taking into account the bilateral preferences of crowdsourcing subjects, the method makes crowdsourcing subjects as satisfied as possible with the current allocation objects so as to guarantee the stability of the allocation results. Then, by using the idea of stable matching, the crowdsourcing task allocation problem is modeled as an optimization problem to find the maximum satisfaction of tasks under stable matching rules. Finally, greedy algorithm is used to solve the problem and a crowdsourcing task allocation scheme is obtained. The rationality and effectiveness of the method are verified by experiments, which shows that the method improves the accuracy of the allocation and effectively reduces the number of invalid allocations, thus improving the quality of crowdsourcing task allocation. 

Key words: crowdsourcing, task allocation, user preference, stable matching, greedy algorithm