Quality assessment of Wikipedia articles without feature engineering

Abstract

As Wikipedia became the largest human knowledge repository, quality measurement of its articles received a lot of attention during the last decade. Most research efforts focused on classification of Wikipedia articles quality by using a different feature set. However, so far, no ``golden feature set" was proposed. In this paper, we present a novel approach for classifying Wikipedia articles by analysing their content rather than by considering a feature set. Our approach uses recent techniques in natural language processing and deep learning, and achieved a comparable result with the state-of-the-art.

DOI: 10.1145/2910896.2910917

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Cite this paper

@article{Dang2016QualityAO, title={Quality assessment of Wikipedia articles without feature engineering}, author={Quang Vinh Dang and Claudia-Lavinia Ignat}, journal={2016 IEEE/ACM Joint Conference on Digital Libraries (JCDL)}, year={2016}, pages={27-30} }