Abstract
We propose an edit-centric approach to assessWikipedia 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 costeffectiveness in terms of data and quality requirements.
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CITATION STYLE
Marrese-Taylor, E., Loyola, P., & Matsuo, Y. (2019). An edit-centric approach forwikipedia article quality assessment. In W-NUT@EMNLP 2019 - 5th Workshop on Noisy User-Generated Text, Proceedings (pp. 381–386). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/d19-5550
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