Affiliation:
1. LORIA, Université de Lorraine / Inria / CNRS
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 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 user 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.
Publisher
Association for Computing Machinery (ACM)
Reference26 articles.
1. Adler B. T. Chatterjee K. De Alfaro L Faella M. Pye I. And Raman V. 2008. Assigning trust to wikipedia content. In Int. Sym. Wikis. ACM. 10.1145/1822258.1822293 Adler B. T. Chatterjee K. De Alfaro L Faella M. Pye I. And Raman V. 2008. Assigning trust to wikipedia content. In Int. Sym. Wikis. ACM. 10.1145/1822258.1822293
2. Anderka M. Stein B. And Lipka N. 2012. Predicting quality flaws in user-generated content: the case of wikipedia. In ) SIGR ACM 981--990. 10.1145/2348283.2348413 Anderka M. Stein B. And Lipka N. 2012. Predicting quality flaws in user-generated content: the case of wikipedia. In ) SIGR ACM 981--990. 10.1145/2348283.2348413
3. Blumenstock J. E. 2008. Size matters: word count as a measure of quality on wikipedia. In WWW.ACM 1095--1096. 10.1145/1367497.1367673 Blumenstock J. E. 2008. Size matters: word count as a measure of quality on wikipedia. In WWW.ACM 1095--1096. 10.1145/1367497.1367673
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献