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 the UNT College of Engineering to the UNT Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 2885 times, with 7 in the last month. More information about this paper can be viewed below.

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

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  • July 2004

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  • Jan. 31, 2011, 2:01 p.m.

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  • Nov. 30, 2023, 2:11 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]. (https://digital.library.unt.edu/ark:/67531/metadc30957/: accessed April 25, 2024), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT College of Engineering.

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