Publication Type

Conference Proceeding Article

Publication Date

8-2014

Abstract

In this paper we study how to summarize travel-related information in forum threads to generate supplementary travel guides. Such summaries presumably can provide additional and more up-to-date information to tourists. Existing multi-document summarization methods have limitations for this task because (1) they do not generate structured summaries but travel guides usually follow a certain template, and (2) they do not put emphasis on named entities but travel guides often recommend points of interest to travelers. To overcome these limitations, we propose to use a latent variable model to align forum threads with the section structure of well-written travel guides. The model also assigns section labels to named entities in forum threads. We then propose to modify an ILP-based summarization method to generate section-specific summaries. Evaluation on threads from Yahoo! Answers shows that our proposed method is able to generate better summaries compared with a number of baselines based on ROUGE scores and coverage of named entities.

Discipline

Databases and Information Systems | Social Media

Research Areas

Data Management and Analytics

Publication

Proceedings of COLING 2014: The 25th International Conference on Computational Linguistics: Technical Papers, Dublin, Ireland, August 23-29 2014

First Page

1670

Last Page

1681

ISBN

9781941643266

Publisher

Association for Computational Linguistics

City or Country

Dublin

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://www.aclweb.org/anthology/C14-1158

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