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- W2888155375 abstract "In this work, we present the first quality flaw prediction study for articles containing the two most frequent verifiability flaws in Spanish Wikipedia: articles which do not cite any references or sources at all (denominated Unreferenced) and articles that need additional citations for verification (so-called Refimprove). Based on the underlying characteristics of each flaw, different state-of-the-art approaches were evaluated. For articles not citing any references, a well-established rule-based approach was evaluated and interesting findings show that some of them suffer from Refimprove flaw instead. Likewise, for articles that need additional citations for verification, the well-known PU learning and one-class classification approaches were evaluated. Besides, new methods were compared and a new feature was also proposed to model this latter flaw. The results showed that new methods such as under-bagged decision trees with sum or majority voting rules, biased-SVM, and centroid-based balanced SVM, perform best in comparison with the ones previously published." @default.
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- W2888155375 date "2018-11-01" @default.
- W2888155375 modified "2023-10-17" @default.
- W2888155375 title "Quality flaw prediction in Spanish Wikipedia: A case of study with verifiability flaws" @default.
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- W2888155375 doi "https://doi.org/10.1016/j.ipm.2018.08.003" @default.
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