z-logo
open-access-imgOpen Access
Quality Assessment of Wikipedia Articles without Feature Engineering
Author(s) -
Quang-Vinh Dang,
ClaudiaLavinia Ignat
Publication year - 2016
Publication title -
hal (le centre pour la communication scientifique directe)
Language(s) - English
Resource type - Conference proceedings
ISSN - 2575-7865
ISBN - 978-1-4503-4229-2
DOI - 10.1145/2910896.2910917
Subject(s) - feature (linguistics) , computer science , feature engineering , quality (philosophy) , set (abstract data type) , information retrieval , artificial intelligence , natural language processing , deep learning , linguistics , philosophy , epistemology , programming language
International audienceAs 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

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom