Toward Extractive Summarization of Online Forum Discussions via Hierarchical Attention Networks

May 25, 2018 ยท Declared Dead ยท ๐Ÿ› The Florida AI Research Society

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Authors Sansiri Tarnpradab, Fei Liu, Kien A. Hua arXiv ID 1805.10390 Category cs.CL: Computation & Language Citations 34 Venue The Florida AI Research Society Last Checked 4 months ago
Abstract
Forum threads are lengthy and rich in content. Concise thread summaries will benefit both newcomers seeking information and those who participate in the discussion. Few studies, however, have examined the task of forum thread summarization. In this work we make the first attempt to adapt the hierarchical attention networks for thread summarization. The model draws on the recent development of neural attention mechanisms to build sentence and thread representations and use them for summarization. Our results indicate that the proposed approach can outperform a range of competitive baselines. Further, a redundancy removal step is crucial for achieving outstanding results.
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