标题:Spatial task allocation based on user trajectory prediction
作者:Jiang, Yun ;He, Wei ;Cui, Lizhen ;Yang, Qian ;Peng, Zhaohui
通讯作者:He, Wei
作者机构:[Jiang, Y] School of Software, Shandong University, Jinan, China;[ He, W] School of Software, Shandong University, Jinan, China;[ Cui, L] School of So 更多
会议名称:13th CCF Conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2018
会议日期:18 August 2018 through 19 August 2018
来源:Communications in Computer and Information Science
出版年:2019
卷:917
页码:386-397
DOI:10.1007/978-981-13-3044-5_28
关键词:Mobile computing environment; Mobile crowdsourcing; Task allocation; Trajectory prediction
摘要:With the rapid development of wireless communication technology and mobile intelligent terminals, location based service has been widely used for its unique features such as mobility, practicality and portability, including mobile crowdsourcing. In mobile computing environment, mobile crowdsourcing task allocation has become a focused research issue. In mobile crowdsourcing, application scenarios are in dynamic state, and workers are also willing to accept tasks. In response to these challenges, this paper proposes a mobile crowdsourcing task allocation strategy based on user trajectory prediction. First, the location points in user historical trajectory data are clustered into regions using k-means algorithm. Then the user’s trajectory is analyzed and excavated to get the user’s mobile pattern. On this basis, we extract mobile rules and calculate the confidence. According to the mobile rules, we predict the region that the user will reach, and finally assign the tasks in the region to him. The prediction based task allocation method proposed in this paper avoids the additional cost that platform need to pay to users, recommends user the task that more suitable for him, and improves the success rate of task allocation. Finally, based on the analysis and simulation experiments of real datasets, the proposed method can effectively predict the location region of users, and at the same time, it can achieve better results than other methods in the situation of task allocation and completion. © Springer Nature Singapore Pte Ltd. 2019.
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85059051812&doi=10.1007%2f978-981-13-3044-5_28&partnerID=40&md5=d8d6d3f1c33d9eb38a18d95918ad91e9
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