Predicting Information Quality Flaws in Wikipedia by Using Classical and Deep Learning Approaches-Reference-Cited by-同舟云学术

Predicting Information Quality Flaws in Wikipedia by Using Classical and Deep Learning Approaches

Published:2020 Issue: Volume: Page:3-18
ISSN:1865-0929
Container-title:Computer Science – CACIC 2019
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Author:

Bazán Pereyra Gerónimo,Cuello Carolina,Capodici Gianfranco,Jofré Vanessa,Ferretti Edgardo^ORCID,Bonnin Rodolfo^ORCID,Errecalde Marcelo^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-48325-8_1

Reference35 articles.

1. Anderka, M.: Analyzing and predicting quality flaws in user-generated content: the case of Wikipedia. Ph.D. thesis, Bauhaus-Universität Weimar, June 2013

2. Anderka, M., Stein, B.: A Breakdown of quality flaws in Wikipedia. In: 2nd Joint WICOW/AIRWeb workshop on Web quality (WebQuality 2012). ACM (2012)

3. Anderka, M., Stein, B.: Overview of the 1st international competition on quality flaw prediction in Wikipedia. In: Forner, P., Karlgren, J., Womser-Hacker, C. (eds.) Working Notes Papers of the CLEF 2012 Evaluation Labs (2012)

4. Anderka, M., Stein, B., Lipka, N.: Detection of text quality flaws as a one-class classification problem. In: Proceedings of the 20th ACM International Conference on Information and Knowledge Management (CIKM 2011). ACM (2011)

5. Anderka, M., Stein, B., Lipka, N.: Towards automatic quality assurance in Wikipedia. In: 20th International Conference on World Wide Web, pp. 5–6. ACM (2011)

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