Cited By
View all- Xing YWang LLi ZZhan Y(2019)Multi-Attribute Crowdsourcing Task Assignment With Stability and SatisfactoryIEEE Access10.1109/ACCESS.2019.29410457(133351-133361)Online publication date: 2019
PIN: Potential Wise Crowd From Million Grassroots
Authors: 
Yao Wu, Tao Huang, Dan Zhao, 
Hong Chen, Cuiping LiAuthors Info & Claims
Yao Wu, Tao Huang, Dan Zhao, Hong Chen, Cuiping LiAuthors Info & ClaimsPages 186 - 195
Abstract
Crowdsourcing proves a viable approach to solve certain large-scale problems by posting tasks distributively to humans and harnessing their knowledge to get results effectively and efficiently. Unfortunately, crowdsourcing suffers from lack of available participants with domain knowledge or skills. In this paper, we propose potential wise crowd (i.e., a crowd with similarity and diversity in domain knowledge) find from million grassroots in social networks. We design and implement a distant-supervision framework to find potential crowdsourcers from existing social networks. A knowledge graph is used to assess the domain knowledge in terms of similarity and diversity. The wise crowd formation is a NP-hard problem and we propose greedy algorithms to approach it. Experimental results show the performance of our framework and algorithms in aspects of effectiveness and efficiency.
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Index Terms
- PIN: Potential Wise Crowd From Million Grassroots
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Published In
November 2017
555 pages
ISBN:9781450353687
DOI:10.1145/3144457
- General Chairs:
- Tao Gu,
- Ramamohanarao Kotagiri,
- Publications Chair:
- Huai Liu
Copyright © 2017 ACM.
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- EAI: The European Alliance for Innovation
- SIGMM: ACM Special Interest Group on Multimedia
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Association for Computing Machinery
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Published: 07 November 2017
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MobiQuitous 2017
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Overall Acceptance Rate 26 of 87 submissions, 30%
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Cited By
View all- Xing YWang LLi ZZhan Y(2019)Multi-Attribute Crowdsourcing Task Assignment With Stability and SatisfactoryIEEE Access10.1109/ACCESS.2019.29410457(133351-133361)Online publication date: 2019
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