Title

Toward Extractive Summarization Of Online Forum Discussions Via Hierarchical Attention Networks

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.

Publication Date

1-1-2017

Publication Title

FLAIRS 2017 - Proceedings of the 30th International Florida Artificial Intelligence Research Society Conference

Number of Pages

288-292

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

85029537926 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85029537926

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