Title | Efficient crowdsourced best objects finding via superiority probability based ordering for decision support systems |
Author | |
Corresponding Author | Yin, Bo |
Publication Years | 2023-08-01
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DOI | |
Source Title | |
ISSN | 0957-4174
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EISSN | 1873-6793
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Volume | 223 |
Abstract | Best objects finding is a fundamental operation in decision support systems and applications. When numerical values of objects cannot be obtained from existing computer systems or in a machine learning manner, crowdsourcing proves a viable approach via harnessing human intelligence for data gathering. Most of existing studies ask crowds to submit pairwise preferences where a large number of crowdsourced questions are produced, thereby incurring huge monetary cost and long latency. To address this issue, we propose a framework for efficient best objects computation by leveraging crowdsourcing to provide object values. The framework employs three query operators ( i.e., top -k, knn, and skyline queries) to compute best objects, and minimizes the number of crowdsourced objects by eagerly pruning non-result objects via superiority probability based ordering. We first propose the concept of superiority probability, which describes the probability that an object is better than or equal to another object from the perspective of statistics. We then explore properties for objects pruning, and propose sequential and parallel ordering techniques for objects crowdsourcing based on the concept of superiority probability. Extensive experimental results show that the proposed framework achieves the promising efficiency in reducing the number of crowdsourced objects and latency. |
Keywords | |
URL | [Source Record] |
Indexed By | |
Language | English
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SUSTech Authorship | Others
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Funding Project | National Natural Science Foun-dation of China[61902040]
; Natural Science Foun-dation of Hunan Province, China["2021JJ30741","2021JJ30743"]
; Scientific Research Foundation of Hunan Provin-cial Education Department, China[20B015]
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WOS Research Area | Computer Science
; Engineering
; Operations Research & Management Science
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WOS Subject | Computer Science, Artificial Intelligence
; Engineering, Electrical & Electronic
; Operations Research & Management Science
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WOS Accession No | WOS:000957287600001
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Publisher | |
ESI Research Field | ENGINEERING
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Data Source | Web of Science
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Citation statistics |
Cited Times [WOS]:0
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Document Type | Journal Article |
Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/524014 |
Department | Department of Computer Science and Engineering |
Affiliation | 1.ChangSha Univ Sci & Technol, Sch Comp & Commun Engn, Changsha 410114, Peoples R China 2.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Shenzhen 518055, Peoples R China |
Recommended Citation GB/T 7714 |
Yin, Bo,Zeng, Weilong,Wei, Xuetao. Efficient crowdsourced best objects finding via superiority probability based ordering for decision support systems[J]. EXPERT SYSTEMS WITH APPLICATIONS,2023,223.
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APA |
Yin, Bo,Zeng, Weilong,&Wei, Xuetao.(2023).Efficient crowdsourced best objects finding via superiority probability based ordering for decision support systems.EXPERT SYSTEMS WITH APPLICATIONS,223.
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MLA |
Yin, Bo,et al."Efficient crowdsourced best objects finding via superiority probability based ordering for decision support systems".EXPERT SYSTEMS WITH APPLICATIONS 223(2023).
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