%0 Conference Paper %1 mola10 %A Mola-Velasco, Santiago M. %B Notebook Papers of CLEF 2010 LABs and Workshops %C Padua, Italy %D 2010 %E Braschler, Martin %E Harman, Donna %E Pianta, Emanuele %K in-thesis machine-learning myown random-forest smola text-classification wikipedia-vandalism %T Wikipedia Vandalism Detection Through Machine Learning: Feature Review and New Proposals - Lab Report for PAN at CLEF 2010 %U http://www.clef2010.org/resources/proceedings/clef2010labs_submission_25.pdf %X 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 cor- pus 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 PAN’10 Wikipedia vandalism detection task. %@ 978-88-904810-0-0

@inproceedings{mola10, abstract = {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 cor- pus 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 PAN’10 Wikipedia vandalism detection task. }, added-at = {2011-07-17T23:33:29.000+0200}, address = {Padua, Italy}, author = {Mola-Velasco, Santiago M.}, biburl = {https://www.bibsonomy.org/bibtex/264687b6ed7a01340e2fc3d44e93ba503/smolav}, booktitle = {Notebook Papers of CLEF 2010 LABs and Workshops}, crossref = {DBLP:conf/clef/2010w}, day = {22-23}, editor = {Braschler, Martin and Harman, Donna and Pianta, Emanuele}, ee = {http://clef2010.org/resources/proceedings/clef2010labs_submission_25.pdf}, interhash = {3c99558d6ec843d5e0b27126b8daaa9e}, intrahash = {64687b6ed7a01340e2fc3d44e93ba503}, isbn = {978-88-904810-0-0}, keywords = {in-thesis machine-learning myown random-forest smola text-classification wikipedia-vandalism}, month = {September}, timestamp = {2011-07-17T23:33:29.000+0200}, title = {{Wikipedia Vandalism Detection Through Machine Learning: Feature Review and New Proposals - Lab Report for PAN at CLEF 2010}}, url = {http://www.clef2010.org/resources/proceedings/clef2010labs_submission_25.pdf}, year = 2010 }