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A Survey on Truth Discovery: Concepts, Methods, Applications, and Opportunities

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dc.contributor.authorWang, S.
dc.contributor.authorZhang, H.
dc.contributor.authorSheng, Q.Z.
dc.contributor.authorLi, X.
dc.contributor.authorSun, Z.
dc.contributor.authorCai, T.
dc.contributor.authorZhang, W.E.
dc.contributor.authorYang, J.
dc.contributor.authorGao, Q.
dc.date.issued2024
dc.description.abstractIn the era of data information explosion, there are different observations on an object (e.g., the height of the Himalayas) from different sources on the web, social sensing, crowd sensing, and data sensing applications. Observations from different sources on an object can conflict with each other due to errors, missing records, typos, outdated data, etc. How to discover truth facts for objects from various sources is essential and urgent. In this paper, we aim to deliver a comprehensive and exhaustive survey on truth discovery problems from the perspectives of concepts, methods, applications, and opportunities. We first systematically review and compare problems from objects, sources, and observations. Based on these problem properties, different methods are analyzed and compared in depth from observation with single or multiple values, independent or dependent sources, static or dynamic sources, and supervised or unsupervised learning, followed by the surveyed applications in various scenarios. For future studies in truth discovery fields, we summarize the code sources and datasets used in above methods. Finally, we point out the potential challenges and opportunities on truth discovery, with the goal of shedding light and promoting further investigation in this area.
dc.description.statementofresponsibilityShuang Wang, He Zhang, Quan Z. Sheng, Xiaoping Li, Zhu Sun, Taotao Cai, Wei Emma Zhang, Jian Yang, Qing Gao
dc.identifier.citationIEEE Transactions on Big Data, 2024; 11(2):314-332
dc.identifier.doi10.1109/TBDATA.2024.3423677
dc.identifier.issn2332-7790
dc.identifier.issn2332-7790
dc.identifier.orcidZhang, W.E. [0000-0002-0406-5974]
dc.identifier.urihttps://hdl.handle.net/2440/146912
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers
dc.relation.granthttp://purl.org/au-research/grants/arc/DP200102298
dc.relation.granthttp://purl.org/au-research/grants/arc/DP230100233
dc.rights© 2024 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See https://www.ieee.org/publications/rights/index.html for more information.
dc.source.urihttp://dx.doi.org/10.1109/tbdata.2024.3423677
dc.subjectbig data; dependent sources, object confidence, source reliability, truth discovery
dc.titleA Survey on Truth Discovery: Concepts, Methods, Applications, and Opportunities
dc.typeJournal article
pubs.publication-statusPublished

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