Quality Assessment of Wikipedia Articles without Feature Engineering - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2016

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 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.
Fichier principal
Vignette du fichier
JCDL2016.pdf (173.74 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01351226 , version 1 (03-08-2016)

Identifiers

Cite

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⟩
376 View
1445 Download

Altmetric

Share

Gmail Facebook X LinkedIn More