Research On Task Assignment In Spatial Crowdsourcing

With the rapid development of mobile devices and shared economic models,this new model of problem solving has aroused widespread concern in the field of databases.The crowdsourcing task is divided into two categories: the traditional crowdsourcing and spatial crowdsourcing.The traditional crowdsourcing does not involve the spatial location of crowdsourcing participants,while spatial crowdsourcing are assigning specific positions to crowdsourcing workers.Task assignment is one of the hot issues in the study of crowdsourcing.This paper mainly studies the problem of task assignment in crowdsourcing.Most of the current related studies consider only crowdsourcing workers and crowdsourcing tasks,but didn't consider where the crowdsourcing is completed and the crowdsourcing tasks that require multiple skills.To this end,this paper first defines the issues related to multi-skills spatial crowdsourcing tasks.Aiming at the existing problems mentioned above in existing related research,based on the existing research,a multi-skill spatial crowdsourcing task assignment model is proposed for multi-skills spatial crowdsourcing task assignment.Based on the multi-skills spatial crowdsourcing task assignment model,aiming at the problem that the existing algorithms GREEDY,g-D&C and ADAPTIVE have fewer tasks and do not consider the platform benefits,the TPC algorithm.for task priority calculation,the WFC algorithm for worker selection,and the MLS algorithm for task location selection are designed respectively.Based on these three algorithms,a multi-skills spatial crowdsourcing task assignment algorithm MS-SCTA is proposed.The experiment verifies with the real dataset Meetup,and uses the existing three algorithms to solve the multi-skills spatial crowdsourcing task assignment problem with the algorithm in this paper.The experimental results show that the proposed MS-SCTA algorithm performs better than the three algorithms in maximizing the task allocation score,platform revenue and task allocation quantity.