2017/12/19 by Yamazaki, Tomoya, Sasaki, Mei, Murakami, Naoya +2 · 1 citation
#FOS: Computer and information sciences #H.3 #Information Retrieval (cs.IR)
paper · doi:10.48550/arxiv.1712.06921
The WSDM Cup 2017 is a binary classification task for classifying Wikidata revisions into vandalism and non-vandalism. This paper describes our method using some machine learning techniques such as under-sampling, feature selection, stacking and ensembles of models. We confirm the validity of each technique by calculating AUC-ROC of models using such techniques and not using them. Additionally, we analyze the results and gain useful insights into improving models for the vandalism detection task. The AUC-ROC of our final submission after the deadline resulted in 0.94412.