Extra-Budget Aware Task Assignment in Spatial Crowdsourcing

被引:0
作者
Wan, Shuhan [1 ]
Zhang, Detian [1 ]
Liu, An [1 ]
Fang, Junhua [1 ]
机构
[1] Soochow Univ, Sch Comp Sci & Technol, Inst Artificial Intelligence, Suzhou, Peoples R China
来源
WEB INFORMATION SYSTEMS ENGINEERING - WISE 2021, PT I | 2021年 / 13080卷
基金
中国国家自然科学基金;
关键词
Spatial crowdsourcing; Task assignment; Extra budget;
D O I
10.1007/978-3-030-90888-1_48
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the prevalence of sharing economy and mobile Internet, spatial crowdsourcing (SC) has been receiving increased attentions recently. A core issue in SC is task assignment, which aims to assign tasks to suitable workers. As workers need to reach the corresponding locations to complete the tasks, they prefer tasks nearby to save travel cost. Therefore, most of the existing solutions for task assignment give workers a fixed range constraint. However, those solutions do not consider the tasks that out of the range, which may make these remote tasks never been completed. Therefore, in this paper, we propose a new problem called extra-budget aware task assignment (EBATA) in spatial crowdsourcing, where extra budget is provided to subsidize the over cost of workers to ensure that the remote tasks have a chance to be accomplished. To address the EBATA problem, two baseline algorithms and two improved greedy algorithms are devised in the paper. The two improved greedy algorithms can heavily reduce the computational time and keep most of the number of matched pairs with the optimal one. Extensive experiments on real dataset verify the effectiveness and efficiency of the proposed methods.
引用
收藏
页码:636 / 644
页数:9
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