Wikipedia Vandalism Detection Through Machine Learning: Feature Review and New Proposals: Lab Report for PAN at CLEF 2010Reportar como inadecuado



 Wikipedia Vandalism Detection Through Machine Learning: Feature Review and New Proposals: Lab Report for PAN at CLEF 2010


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Wikipedia is an online encyclopedia that anyone can edit. In this open model, some people edits with the intent of harming the integrity of Wikipedia. This is known as vandalism. We extend the framework presented in Potthast, Stein, and Gerling, 2008 for Wikipedia vandalism detection. In this approach, several vandalism indicating features are extracted from edits in a vandalism corpus and are fed to a supervised learning algorithm. The best performing classifiers were LogitBoost and Random Forest. Our classifier, a Random Forest, obtained an AUC of 0.92236, ranking in the first place of the PAN10 Wikipedia vandalism detection task.



Autor: Santiago M. Mola-Velasco

Fuente: https://archive.org/







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