Publication Type

Conference Proceeding Article

Publication Date

7-2011

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.

Discipline

Databases and Information Systems

Research Areas

Data Management and Analytics

Publication

Proceedings on the Conference on Empirical Methods in Natural Language Processing (EMNLP)

First Page

1137

Last Page

1146

Publisher

Association for Computational Linguistics

City or Country

Edinburgh, Scotland

Additional URL

http://aclweb.org/anthology/D/D11/D11-1105.pdf

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