Abstract
Truth discovery is an important component of data cleaning and information integration. However, in the absence of knowledge, some truth could not be found from databases themselves. A possible solution is to involve crowds to find all the truth with the knowledge of crowds. In this paper, we propose a truth discovery framework based on active learning model with crowdsourcing. First, we give the basic voting algorithm BVote . Then we present the simple crowding-based truth discovery framework STDA based on BVote. Experimental results show that the STDA framework for truth discovery has improved significantly in accuracy with minimal efforts of workers.
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References
Yin, X., Han, J., Yu, P.S.: Truth discovery with multiple conflicting information providers on the web. In: KDD 2007 (2007)
Galland, A., Abiteboul, S., Marian, A., Senellart, P.: Corroborating information from disagreeing views. WSDM 2010 (2010)
Dong, X.L., Berti-Equille, L., Hu, Y., Srivastava, D.: Global detection of complex copying relationships between sources. In: VLDB 2010 (2010)
Howe, J.: The rise of crowdsourcing. Wired Magazine 14(6), 1–4 (2006)
Cohn, D.A., Ghahramani, Z., Jordan, M.I.: Active learning with statistical models. arXiv preprint cs/9603104 (1996)
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© 2014 Springer International Publishing Switzerland
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Ye, C., Wang, H., Gao, H., Li, J., Xie, H. (2014). Truth Discovery Based on Crowdsourcing. In: Li, F., Li, G., Hwang, Sw., Yao, B., Zhang, Z. (eds) Web-Age Information Management. WAIM 2014. Lecture Notes in Computer Science, vol 8485. Springer, Cham. https://doi.org/10.1007/978-3-319-08010-9_48
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DOI: https://doi.org/10.1007/978-3-319-08010-9_48
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08009-3
Online ISBN: 978-3-319-08010-9
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