We propose an edit-centric approach to assess Wikipedia article quality as a complementary alternative to current full document-based techniques. Our model consists of a main classifier equipped with an auxiliary generative module which, for a given edit, jointly provides an estimation of its quality and generates a description in natural language. We performed an empirical study to assess the feasibility of the proposed model and its cost-effectiveness in terms of data and quality requirements.
@article{arxiv.1909.08880,
title = {An Edit-centric Approach for Wikipedia Article Quality Assessment},
author = {Edison Marrese-Taylor and Pablo Loyola and Yutaka Matsuo},
journal= {arXiv preprint arXiv:1909.08880},
year = {2019}
}