Graph-based Ranking Algorithms for Sentence Extraction, Applied to Text Summarization

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Abstract: This paper presents an innovative unsupervised method for automatic sentence extraction using graph-based ranking algorithms. We evaluate the method in the context of a text summarization task, and show that the results obtained compare favorably with previously published results on established benchmarks.

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4 p.

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Mihalcea, Rada, 1974- July 2004.

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This paper is part of the collection entitled: UNT Scholarly Works and was provided by UNT College of Engineering to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 2053 times , with 33 in the last month . More information about this paper can be viewed below.

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The UNT College of Engineering promotes intellectual and scholarly pursuits in the areas of computer science and engineering, preparing innovative leaders in a variety of disciplines. The UNT College of Engineering encourages faculty and students to pursue interdisciplinary research among numerous subjects of study including databases, numerical analysis, game programming, and computer systems architecture.

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Abstract: This paper presents an innovative unsupervised method for automatic sentence extraction using graph-based ranking algorithms. We evaluate the method in the context of a text summarization task, and show that the results obtained compare favorably with previously published results on established benchmarks.

Physical Description

4 p.

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  • Forty-Second Annual Meeting of the Association for Computational Linguistics, 2004, Barcelona, Spain

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UNT Scholarly Works

Materials from the UNT community's research, creative, and scholarly activities and UNT's Open Access Repository. Access to some items in this collection may be restricted.

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  • July 2004

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  • Jan. 31, 2011, 2:01 p.m.

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  • April 25, 2013, 12:25 p.m.

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Mihalcea, Rada, 1974-. Graph-based Ranking Algorithms for Sentence Extraction, Applied to Text Summarization, paper, July 2004; [Stroudsburg, Pennsylvania]. (digital.library.unt.edu/ark:/67531/metadc30957/: accessed December 15, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.