Online delivery route recommendation in spatial crowdsourcing

Online delivery route recommendation in spatial crowdsourcing World Wide Web https://doi.org/10.1007/s11280-018-0563-4 Online delivery route recommendation in spatial crowdsourcing 1 1 1 2 Dezhi Sun · Ke Xu · Hao Cheng · Yuanyuan Zhang · 1 1 1 Tianshu Song · Rui Liu · Yi Xu Received: 25 February 2018 / Revised: 30 March 2018 / Accepted: 5 April 2018 © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract With the emergence of many crowdsourcing platforms, crowdsourcing has gained much attention. Spatial crowdsourcing is a rapidly developing extension of the traditional crowdsourcing, and its goal is to organize workers to perform spatial tasks. Route recom- mendation is an important concern in spatial crowdsourcing. In this paper, we define a novel problem called the Online Delivery Route Recommendation (OnlineDRR) problem, in which the income of a single worker is maximized under online scenarios. It is proved that no deterministic online algorithm for this problem has a constant competitive ratio. We This article belongs to the Topical Collection: Special Issue on Big Data Management and Intelligent Analytics Guest Editors: Junping Du, Panos Kalnis, Wenling Li, and Shuo Shang Rui Liu lr@buaa.edu.cn Dezhi Sun buaasun@buaa.edu.cn Ke Xu kexu@buaa.edu.cn Hao Cheng chengh@buaa.edu.cn Yuanyuan Zhang zhangyuanyuan@datang.com Tianshu Song songts@buaa.edu.cn Yi http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png World Wide Web Springer Journals

Online delivery route recommendation in spatial crowdsourcing

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Publisher
Springer US
Copyright
Copyright © 2018 by Springer Science+Business Media, LLC, part of Springer Nature
Subject
Computer Science; Information Systems Applications (incl.Internet); Database Management; Operating Systems
ISSN
1386-145X
eISSN
1573-1413
D.O.I.
10.1007/s11280-018-0563-4
Publisher site
See Article on Publisher Site

Abstract

World Wide Web https://doi.org/10.1007/s11280-018-0563-4 Online delivery route recommendation in spatial crowdsourcing 1 1 1 2 Dezhi Sun · Ke Xu · Hao Cheng · Yuanyuan Zhang · 1 1 1 Tianshu Song · Rui Liu · Yi Xu Received: 25 February 2018 / Revised: 30 March 2018 / Accepted: 5 April 2018 © Springer Science+Business Media, LLC, part of Springer Nature 2018 Abstract With the emergence of many crowdsourcing platforms, crowdsourcing has gained much attention. Spatial crowdsourcing is a rapidly developing extension of the traditional crowdsourcing, and its goal is to organize workers to perform spatial tasks. Route recom- mendation is an important concern in spatial crowdsourcing. In this paper, we define a novel problem called the Online Delivery Route Recommendation (OnlineDRR) problem, in which the income of a single worker is maximized under online scenarios. It is proved that no deterministic online algorithm for this problem has a constant competitive ratio. We This article belongs to the Topical Collection: Special Issue on Big Data Management and Intelligent Analytics Guest Editors: Junping Du, Panos Kalnis, Wenling Li, and Shuo Shang Rui Liu lr@buaa.edu.cn Dezhi Sun buaasun@buaa.edu.cn Ke Xu kexu@buaa.edu.cn Hao Cheng chengh@buaa.edu.cn Yuanyuan Zhang zhangyuanyuan@datang.com Tianshu Song songts@buaa.edu.cn Yi

Journal

World Wide WebSpringer Journals

Published: May 28, 2018

References

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