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A Joint Model for Multimodal Document Quality Assessment

2019-01-04
Aili Shen, Bahar Salehi, Timothy Baldwin, Jianzhong Qi

Abstract

The quality of a document is affected by various factors, including grammaticality, readability, stylistics, and expertise depth, making the task of document quality assessment a complex one. In this paper, we explore this task in the context of assessing the quality of Wikipedia articles and academic papers. Observing that the visual rendering of a document can capture implicit quality indicators that are not present in the document text — such as images, font choices, and visual layout — we propose a joint model that combines the text content with a visual rendering of the document for document quality assessment. Experimental results over two datasets reveal that textual and visual features are complementary, achieving state-of-the-art results.

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URL

https://arxiv.org/abs/1901.01010

PDF

https://arxiv.org/pdf/1901.01010


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