An end-to-end learning solution for assessing the quality of Wikipedia articles

Abstract

Wikipedia is considered as the largest knowledge repository in the history of humanity and plays a crucial role in modern daily life. Assigning the correct quality class to Wikipedia articles is an important task in order to provide guidance for both authors and readers of Wikipedia. The manual review cannot cope with the editing speed of Wikipedia. An automatic classification is required to classify the quality of Wikipedia articles. Most existing approaches rely on traditional machine learning with manual feature engineering, which requires a lot of expertise and effort. Furthermore, it is known that there is no general perfect feature set because information leak always occurs in feature extraction phase. Also, for each language of Wikipedia, a new feature set is required.