Abstract
A very example of web 2.0 application is Wikipedia, an online encyclopedia where anyone can edit and share information. However, blatantly unproductive edits greatly undermine the quality of Wikipedia. Their irresponsible acts force editors to waste time undoing vandalisms. For the purpose of improving information quality on Wikipedia and freeing the maintainer from such repetitive tasks, machine learning methods have been proposed to detect vandalism automatically. However, most of them focused on mining new features which seem to be inexhaustible to be discovered. Therefore, the question of how to make the best use of these features needs to be tackled. In this paper, we leverage feature transformation techniques to analyze the features and propose a framework using these methods to enhance detection. Experiment results on the public dataset PAN-WVC-10 show that our method is effective and it provides another useful method to help detect vandalism in Wikipedia.
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Chang, T., Lin, H., Lin, Y. (2012). Feature Transformation Method Enhanced Vandalism Detection in Wikipedia. In: Hou, Y., Nie, JY., Sun, L., Wang, B., Zhang, P. (eds) Information Retrieval Technology. AIRS 2012. Lecture Notes in Computer Science, vol 7675. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35341-3_16
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DOI: https://doi.org/10.1007/978-3-642-35341-3_16
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