NDLI: Towards More Effective Text Summarization Based on Textual Association Networks

Content Provider	IEEE Xplore Digital Library
Author	Yuhui Tao Shuigeng Zhou Wai Lam Jihong Guan
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Fudan Univ., Shanghai, China (Yuhui Tao; Shuigeng Zhou) \|\| Dept. of Syst. Eng. & Eng. Manage., Chinese Univ. of Hong Kong, Hong Kong, China (Wai Lam) \|\| Dept. of Comput. Sci. & Technol., Tongji Univ., Shanghai, China (Jihong Guan)
Abstract	This paper proposes new text summarization approaches based on textual unit association networks. Textual units refer to words, phrases, sentences, or paragraphs. Intuitively, textual units containing much co-occurrence information are semantically more salient in a document. We construct two kinds of textual association networks, namely, word-based association network and sentence-based association network. For the former, we propose anew approach to computing the word weights and sentence weights.For the latter, we develop a new scheme to score each sentence based on its co-occurrence information. Extensive experiments on benchmark data show that our proposed approaches can achieve better summarization performance than the existing methods. Our approaches are unsupervised, independent of languages, and efficient for different text genre.
Starting Page	235
Ending Page	240
File Size	227937
Page Count	6
File Format	PDF
ISBN	9780769534015
DOI	10.1109/SKG.2008.17
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-03
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer science Knowledge engineering Intelligent networks Content based retrieval Information processing Search engines Frequency Systems engineering and theory Data mining Research and development management
Content Type	Text
Resource Type	Article

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