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Paper · arXiv

Hierarchical Graph Convolutional Network Approach for Detecting Low-Quality Documents

Consistency within a document is a crucial feature indicative of its quality. Recently, within the vast amount of information produced across various media, there exists a significant number of low-quality documents that either lack internal consistency or contain content utterly unrelated to their headlines. Such low-quality documents induce fatigue in readers and undermine the credibility of the media source that provided them. Consequently, research to automatically detect these low-quality documents based on natural language processing is imperative. In this study, we introduce a hierarchical graph convolutional network (HGCN) that can detect internal inconsistencies within a document...

AuthorsJaeyoung Lee, Joonwon Jang, Misuk Kim
Primary categorycs.AI
Published15 October 2026
Last updated at source15 October 2026
cs.AI
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