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2011
ACM

Semi-supervised truth discovery

8 years 1 months ago
Semi-supervised truth discovery
Accessing online information from various data sources has become a necessary part of our everyday life. Unfortunately such information is not always trustworthy, as different sources are of very different qualities and often provide inaccurate and conflicting information. Existing approaches attack this problem using unsupervised learning methods, and try to infer the confidence of the data value and trustworthiness of each source from each other by assuming values provided by more sources are more accurate. However, because false values can be widespread through copying among different sources and out-of-date data often overwhelm up-to-date data, such bootstrapping methods are often ineffective. In this paper we propose a semi-supervised approach that finds true values with the help of ground truth data. Such ground truth data, even in very small amount, can greatly help us identify trustworthy data sources. Unlike existing studies that only provide iterative algorithms, we derive t...
Xiaoxin Yin, Wenzhao Tan
Added 15 May 2011
Updated 15 May 2011
Type Journal
Year 2011
Where WWW
Authors Xiaoxin Yin, Wenzhao Tan
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