NDLI: Exploiting Surface, Content and Relevance Features for Learning-Based Extractive Summarization

Content Provider	IEEE Xplore Digital Library
Author	Mingli Wu Wenjie Li Furu Wei Qin Lu Kam-Fai Wong
Copyright Year	2007
Description	Author affiliation: Chinese Univ. of Hong, Shatin (Mingli Wu)
Abstract	Extractive summarization is to identify whether a sentence should be selected for inclusion in the summary or not. It can be transformed into a classification task. In this paper, we explore various features under a learning-based classification framework, including basic surface features, content features a sentence may represent and the features indicating the relevance among sentences. While surface and content features are about extrinsic and intrinsic aspects of a sentence itself, relevance features describe the strength of sentence related-ness. Sentences processed by classifiers are then feed to a re-ranking algorithm. The ones with higher priority are included in the summary. Experiments show that the proposed framework and the integrated features achieve competitive results on DUC 2001 document sets when evaluated by ROUGE. We find that relevance features are able to improve the summarization performance obviously.
Starting Page	234
Ending Page	241
File Size	9463300
Page Count	8
File Format	PDF
ISBN	9781424416103
DOI	10.1109/NLPKE.2007.4368082
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-30
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Costs Feature extraction Frequency Table lookup Feeds Statistics Tellurium Testing
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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