4.5 Article

General framework, opportunities and challenges for crowdsourcing techniques: A Comprehensive survey

期刊

JOURNAL OF SYSTEMS AND SOFTWARE
卷 167, 期 -, 页码 -

出版社

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jss.2020.110611

关键词

Crowdsourcing; Framework; Incentives; Decomposition; Aggregation; Reputation

资金

  1. National Key R&D Program of China [2018YFB1004703]
  2. National Natural Science Foundation of China [61872238, 61672353]
  3. Shanghai Science and Technology Fund [17510740200]
  4. Huawei Innovation Research Program [HO2018085286]
  5. State Key Laboratory of Air Traffic Management System and Technology [SKLATM20180X]
  6. Tencent Social Ads Rhino-Bird Focused Research Program
  7. CCF-Huawei Database System Innovation Research Plan [CCF-Huawei DBIR2019002A]

向作者/读者索取更多资源

Crowdsourcing, a distributed human problem-solving paradigm is an active research area which has attracted significant attention in the fields of computer science, business, and information systems. Crowdsourcing holds novelty with advantages like open innovation, scalability, and cost-efficiency. Although considerable research work is performed, however, a survey on the crowdsourcing process-technology has not been divulged yet. In this paper, we present a systematic survey of crowdsourcing in focussing emerging techniques and approaches for improving conventional and developing future crowdsourcing systems. We first present a simplified definition of crowdsourcing. Then, we propose a framework based on three major components, synthesize a wide spectrum of existing studies for various dimensions of the framework. According to the framework, we first introduce the initialization step, including task design, task settings, and incentive mechanisms. Next, in the implementation step, we look into task decomposition, crowd and platform selection, and task assignment. In the last step, we discuss different answer aggregation techniques, validation methods and reward tactics, and reputation management. Finally, we identify open issues and suggest possible research directions for the future. (C) 2020 Elsevier Inc. All rights reserved.

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