Abstract: Most existing crowdsourcing researches previously use top workers to complete tasks,i.e.,crowdsourcing platforms always assign workers with the highest skill levels and reputation to tasks.However,in reality,most of the workers have relatively low skill levels and reputation,resulting in a large number of unassignable tasks and workers without tasks to do in crowdsourcing platforms.The main reasons for the problem are as follows:(1)complex tasks have high skill level requirements and the number of professional workers is small,so workers with insufficient skill levels are unable to complete complex tasks,which causes a large number of tasks fail to be assigned;(2)tasks are priority assigned to workers with high skill levels and high reputation,while workers with relatively low skill levels and reputation are not available to be assigned because they cannot meet the task requirements.In the real crowdsourcing platform,we find that many complex tasks have sufficient budgets and workers can improve their skill levels through collaboration.On the basis of these practical observations,we design a worker collaboration model in this paper.When the platform lacks of workers who meet the task requirements,the model allows workers with inadequate skill levels to participate in the team and collaborate to achieve the task skill level requirements before being assigned the task.Finally,the experiments are carried out on a real dataset and the results show that the proposed model can improve the success rate of task assignment and also reduce the budget cost of requesters,increase the income of workers.

Key words: Crowdsourcing, Complex tasks, Task allocation, Cooperation of workers, Skill levels