Volume 4 Number 5 (Sep. 2015)
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IJCCE 2015 Vol.4(5): 363-370 ISSN: 2010-3743
DOI: 10.17706/IJCCE.2015.4.5.363-370

Automatic Microblog Summarization Based on Unsupervised Key-Bigram Extraction

Yufang Wu, Heng Zhang, Bo Xu, Hongwei Hao, Chenglin Liu
Abstract—Microblog summarization can save large amount of time for users in browsing. In this paper, we propose an automatic microblog summarization method based on unsupervised key-bigram extraction. Firstly, we extract a key-bigram set to discover the key aspects of posts by three unsupervised key-bigram extractor based on Hybrid TF-IDF, TextRank and Latent Dirichlet Allocation (LDA). Secondly, we rank sentences by overlap similarity and mutual information strategies based on the key-bigram set. Top ranked salient sentences with redundancy removal are selected as summaries. Compared with some other text content based summarizers, the proposed method was shown to perform superiorly in experiments on SinaWeibo and Twitter datasets.

Index Terms—Automatic summarization, key-bigram extraction, microblog, sentence extraction.

The authors are with the Institute of Automation, Chinese Academy of Sciences, 95 Zhongguancun East Road, Beijing, P.R. China.

Cite:Yufang Wu, Heng Zhang, Bo Xu, Hongwei Hao, Chenglin Liu, "Automatic Microblog Summarization Based on Unsupervised Key-Bigram Extraction," International Journal of Computer and Communication Engineering vol. 4, no. 5, pp. 363-370, 2015.

General Information

ISSN: 2010-3743 (Online)
Abbreviated Title: Int. J. Comput. Commun. Eng.
Frequency: Quarterly
Editor-in-Chief: Dr. Maode Ma
Abstracting/ Indexing: INSPEC, CNKI, Google Scholar, Crossref, EBSCO, ProQuest, and Electronic Journals Library
E-mail: ijcce@iap.org
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