Quantifying the Limits and Success of Extractive Summarization Systems Across Domains

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This paper analyzes the topic identification stage of single-document automatic text summarization across four different domains, consisting of newswire, literary, scientific and legal documents.

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9 p.

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Ceylan, Hakan; Mihalcea, Rada, 1974-; Ozertem, Umut; Lloret, Elena & Palomar, Manuel June 2010.

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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 98 times . More information about this paper can be viewed below.

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This paper analyzes the topic identification stage of single-document automatic text summarization across four different domains, consisting of newswire, literary, scientific and legal documents.

Physical Description

9 p.

Notes

Abstract: This paper analyzes the topic identification stage of single-document automatic text summarization across four different domains, consisting of newswire, literary, scientific and legal documents. The authors present a study that explores the summary space of each domain via an exhaustive search strategy, and finds the probability density function (pdf) of the ROUGE score distributions for each domain. The authors then use this pdf to calculate the percentile rank of extractive summarization systems. Their results introduce a new way to judge the success of automatic summarization systems and bring quantified explanations to questions such as why it was so hard for the systems to date to have a statistically significant improvement over the lead baseline in the news domain.

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  • Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2010, Los Angeles, California, United States

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UNT Scholarly Works

The Scholarly Works Collection is home to materials from the University of North Texas community's research, creative, and scholarly activities and serves as UNT's Open Access Repository. It brings together articles, papers, artwork, music, research data, reports, presentations, and other scholarly and creative products representing the expertise in our university community. Access to some items in this collection may be restricted.

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  • June 2010

Added to The UNT Digital Library

  • Jan. 31, 2011, 2:01 p.m.

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  • April 28, 2014, 2:05 p.m.

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Ceylan, Hakan; Mihalcea, Rada, 1974-; Ozertem, Umut; Lloret, Elena & Palomar, Manuel. Quantifying the Limits and Success of Extractive Summarization Systems Across Domains, paper, June 2010; (digital.library.unt.edu/ark:/67531/metadc31026/: accessed April 26, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.