中文版 | English
Title

Efficient crowdsourced best objects finding via superiority probability based ordering for decision support systems

Author
Corresponding AuthorYin, Bo
Publication Years
2023-08-01
DOI
Source Title
ISSN
0957-4174
EISSN
1873-6793
Volume223
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
SUSTech Authorship
Others
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]
WOS Research Area
Computer Science ; Engineering ; Operations Research & Management Science
WOS Subject
Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Operations Research & Management Science
WOS Accession No
WOS:000957287600001
Publisher
ESI Research Field
ENGINEERING
Data Source
Web of Science
Citation statistics
Cited Times [WOS]:0
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/524014
DepartmentDepartment 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.
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.
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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