Quality Assessment of Wikipedia Articles: A Deep Learning Approach

Quang-Vinh Dang 1 Claudia-Lavinia Ignat 1
1 COAST - Web Scale Trustworthy Collaborative Service Systems
Inria Nancy - Grand Est, LORIA - NSS - Department of Networks, Systems and Services
Abstract : Wikipedia is indeed a very important knowledge sharing platform. However, since its start in 2001, the quality of Wikipedia is questioned because its content is created potentially by everyone who can access to the Internet. Currently, the quality of Wikipedia articles is assessed by human judgement. The method is not scalable up to huge size and fast changing speed of Wikipedia today. An automatic quality classifier for Wikipedia articles is required to support users to choose high quality articles for reading and to notify authors for improving their products. While other existing approaches are based on manually predefined specific feature set, we present our approach of using deep learning to automatically represent Wikipedia articles for quality classification.
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Quang-Vinh Dang, Claudia-Lavinia Ignat. Quality Assessment of Wikipedia Articles: A Deep Learning Approach. ACM SIGWEB Newsletter (ACM Digital Library), Association for Computing Machinery (ACM), 2016, 〈10.1145/2996442.2996447〉. 〈hal-01393227〉

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