A Survey of Spatial Crowdsourcing

被引:68
作者
Gummidi, Srinivasa Raghavendra Bhuvan [1 ]
Xie, Xike [2 ]
Pedersen, Torben Bach [1 ]
机构
[1] Aalborg Univ, Dept Comp Sci, DK-9220 Aalborg, Denmark
[2] Univ Sci & Technol China, Sch Comp Sci & Technol, Hefei, Anhui, Peoples R China
来源
ACM TRANSACTIONS ON DATABASE SYSTEMS | 2019年 / 44卷 / 02期
基金
中国国家自然科学基金;
关键词
Algorithms; task scheduling; spatial crowdsourcing; task assignment; task matching; rewards; incentive mechanism; quality assurance; location privacy; spatial databases; ONLINE TASK ASSIGNMENT; TRUTH DISCOVERY;
D O I
10.1145/3291933
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Widespread use of advanced mobile devices has led to the emergence of a new class of crowdsourcing called spatial crowdsourcing. Spatial crowdsourcing advances the potential of a crowd to perform tasks related to real-world scenarios involving physical locations, which were not feasible with conventional crowdsourcing methods. The main feature of spatial crowdsourcing is the presence of spatial tasks that require workers to be physically present at a particular location for task fulfillment. Research related to this new paradigm has gained momentum in recent years, necessitating a comprehensive survey to offer a bird's-eye view of the current state of spatial crowdsourcing literature. In this article, we discuss the spatial crowdsourcing infrastructure and identify the fundamental differences between spatial and conventional crowdsourcing. Furthermore, we provide a comprehensive view of the existing literature by introducing a taxonomy, elucidate the issues/challenges faced by different components of spatial crowdsourcing, and suggest potential research directions for the future.
引用
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页数:46
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