Generating aspect-oriented multi-document summarization with event-aspect model

Peng Li, Yinglin Wang, Wei Gao, Jing Jiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

29 Citations (Scopus)

Abstract

In this paper, we propose a novel approach to automatic generation of aspect-oriented summaries from multiple documents. We first develop an event-aspect LDA model to cluster sentences into aspects. We then use extended LexRank algorithm to rank the sentences in each cluster. We use Integer Linear Programming for sentence selection. Key features of our method include automatic grouping of semantically related sentences and sentence ranking based on extension of random walk model. Also, we implement a new sentence compression algorithm which use dependency tree instead of parser tree. We compare our method with four baseline methods. Quantitative evaluation based on Rouge metric demonstrates the effectiveness and advantages of our method.

Original languageEnglish
Title of host publicationEMNLP 2011 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference
Pages1137-1146
Number of pages10
Publication statusPublished - 3 Oct 2011
EventConference on Empirical Methods in Natural Language Processing, EMNLP 2011 - Edinburgh, United Kingdom
Duration: 27 Jul 201131 Jul 2011

Publication series

NameEMNLP 2011 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference

Other

OtherConference on Empirical Methods in Natural Language Processing, EMNLP 2011
CountryUnited Kingdom
CityEdinburgh
Period27/7/1131/7/11

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ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems

Cite this

Li, P., Wang, Y., Gao, W., & Jiang, J. (2011). Generating aspect-oriented multi-document summarization with event-aspect model. In EMNLP 2011 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference (pp. 1137-1146). (EMNLP 2011 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference).