Skip to Main content Skip to Navigation
New interface
Conference papers

Quality Assessment of Wikipedia Articles without Feature Engineering

Quang-Vinh Dang 1, * Claudia-Lavinia Ignat 1 
* Corresponding author
1 COAST - Web Scale Trustworthy Collaborative Service Systems
Inria Nancy - Grand Est, LORIA - NSS - Department of Networks, Systems and Services
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 fo-cused 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.
Complete list of metadata

Cited literature [21 references]  Display  Hide  Download
Contributor : Claudia-Lavinia Ignat Connect in order to contact the contributor
Submitted on : Wednesday, August 3, 2016 - 7:32:28 AM
Last modification on : Wednesday, April 6, 2022 - 3:48:24 PM
Long-term archiving on: : Tuesday, November 8, 2016 - 8:12:53 PM


Files produced by the author(s)



Quang-Vinh Dang, Claudia-Lavinia Ignat. Quality Assessment of Wikipedia Articles without Feature Engineering. Proceedings of the 16th ACM/IEEE-CS on Joint Conference on Digital Libraries, Jun 2016, Newark, United States. pp.27-30, ⟨10.1145/2910896.2910917⟩. ⟨hal-01351226⟩



Record views


Files downloads