Conference Proceeding Article
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.
Databases and Information Systems | Social Media
Data Management and Analytics
Proceedings of COLING 2014: The 25th International Conference on Computational Linguistics: Technical Papers, Dublin, Ireland, August 23-29 2014
Association for Computational Linguistics
City or Country
YANG, Liu; JIANG, Jing; HUANG, Lifu; QIU, Minghui; and LIAO, Lizi.
Generating Supplementary Travel Guides from Social Media. (2014). Proceedings of COLING 2014: The 25th International Conference on Computational Linguistics: Technical Papers, Dublin, Ireland, August 23-29 2014. 1670-1681. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/2413
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