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Dong, Yu, Jiang, Liangxiao, Li, Chaoqun (2022) Improving data and model quality in crowdsourcing using co-training-based noise correction. Information Sciences, 583. 174-188 doi:10.1016/j.ins.2021.11.021

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Reference TypeJournal (article/letter/editorial)
TitleImproving data and model quality in crowdsourcing using co-training-based noise correction
JournalInformation Sciences
AuthorsDong, YuAuthor
Jiang, LiangxiaoAuthor
Li, ChaoqunAuthor
Year2022 (January)Volume583
PublisherElsevier BV
DOIdoi:10.1016/j.ins.2021.11.021Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID13447722Long-form Identifiermindat:1:5:13447722:2
GUID0
Full ReferenceDong, Yu, Jiang, Liangxiao, Li, Chaoqun (2022) Improving data and model quality in crowdsourcing using co-training-based noise correction. Information Sciences, 583. 174-188 doi:10.1016/j.ins.2021.11.021
Plain TextDong, Yu, Jiang, Liangxiao, Li, Chaoqun (2022) Improving data and model quality in crowdsourcing using co-training-based noise correction. Information Sciences, 583. 174-188 doi:10.1016/j.ins.2021.11.021
In(2022) Information Sciences Vol. 583. Elsevier BV

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