CLSep 19, 2019

An Edit-centric Approach for Wikipedia Article Quality Assessment

arXiv:1909.08880v1995 citations
Originality Incremental advance
AI Analysis

This addresses quality control for Wikipedia editors and readers, but appears incremental as it builds on existing assessment techniques.

The authors tackled Wikipedia article quality assessment by proposing an edit-centric model that jointly estimates edit quality and generates natural language descriptions, finding it to be a cost-effective complementary approach to full document-based methods.

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.

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