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| 时空众包数据管理技术研究综述 |
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童咏昕1,2, 袁野3, 成雨蓉3, 陈雷4, 王国仁3
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1.软件开发环境国家重点实验室(北京航空航天大学), 北京 100191;2.北京航空航天大学 计算机学院, 北京 100191;3.东北大学 计算机科学与工程学院, 辽宁 沈阳 110004;4.香港科技大学 计算机科学与工程学系, 香港
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| 摘要: |
| 近年来，众包为传统数据管理提供了一种通过汇聚群体智慧求解问题的新模式，并成为当前数据库领域的研究热点之一.特别是随着移动互联网技术与共享经济模式的快速发展，众包技术已融入到各类具有时空数据的应用场景中，例如各类O2O（online-to-offline）应用、实时交通监控与动态物流管理等.简言之，这种应用众包技术处理时空数据的方式称为时空众包数据管理.对近期在时空众包数据管理方面的研究工作进行综述，首先阐述了时空众包的概念，解释了其与传统众包技术的关系，并介绍了各类典型的时空众包应用；随后描述了时空众包应用平台的工作流程及其任务特点；然后讨论了时空众包数据管理的3项核心研究问题和3类应用技术；最后，总结了时空众包数据管理技术的研究现状并展望了其未来潜在的研究方向，为相关研究人员提供了有价值的参考. |
| 关键词: 时空众包 共享经济 O2O模式 任务分配 质量控制 隐私保护 |
| DOI：10.13328/j.cnki.jos.005140 |
| 分类号: |
| 基金项目:国家重点基础研究发展计划（973）（2014CB340300）；国家自然科学基金（61502021，61622202，61572119，U1401256）；北京航空航天大学软件开发环境国家重点实验室开放课题（SKLSDE-2016ZX-13） |
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| Survey on Spatiotemporal Crowdsourced Data Management Techniques |
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TONG Yong-Xin1,2, YUAN Ye3, CHENG Yu-Rong3, CHEN Lei4, WANG Guo-Ren3
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1.State Key Laboratory of Software Development Environmnt(Beihang University), Beijing 100191, China;2.School of Computer Science and Engineering, Beihang University, Beijing 100191, China;3.School of Computer Science and Engineering, Northeastern University, Shenyang 110004, China;4.Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong, China
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| Abstract: |
| In recent years, crowdsourcing, which utilizes the intelligence of crowds to solve problems, provides a novel data processing paradigm for traditional data management challenges and has become one of the hottest research topics. In particular, due to the rapid development of mobile Internet and sharing economy, crowdsourcing not only becomes a new approach for data collection, but is also integrated into all kinds of application scenarios especially spatiotemporal data management such as online-to-offline (O2O) applications, real-time traffic monitoring, and logistics management. In this paper, a survey is provided on existing research of spatiotemporal crowdsourcing. First of all, the concept and representative applications of spatiotemporal crowdsourcing is described, and its relationship with traditional crowdsourcing is explained. Then, the workflow of spatiotemporal crowdsourcing is illustrated. Furthermore, three core research problems and three categories of techniques of spatiotemporal crowdsourcing are discussed. Finally, the state-of-the-art studies of spatiotemporal crowdsourcing are summarized and promising future research directions for the research community are presented. |
| Key words: spatiotemporal crowdsourcing sharing economy O2O mode task assignment quality control privacy protection |
