Publication Type
Conference Proceeding Article
Version
publishedVersion
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
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
Citation
LI, Peng; WANG, Yinglin; GAO, Wei; and JIANG, Jing.
Generating Aspect-oriented Multi-document Summarization with Event-Aspect Model. (2011). Proceedings on the Conference on Empirical Methods in Natural Language Processing (EMNLP). 1137-1146.
Available at: https://ink.library.smu.edu.sg/sis_research/1378
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://aclweb.org/anthology/D/D11/D11-1105.pdf