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
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