TextRank: Bringing Order into Texts

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In this paper, the authors introduce TextRank, a graph-based ranking model for text processing, and show how this model can be successfully used in natural language applications.

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8 p.

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Mihalcea, Rada, 1974- & Tarau, Paul 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 8634 times , with 156 in the last month . More information about this paper can be viewed below.

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Description

In this paper, the authors introduce TextRank, a graph-based ranking model for text processing, and show how this model can be successfully used in natural language applications.

Physical Description

8 p.

Notes

Abstract: In this paper, we introduce TextRank, a graph-based ranking model for text processing, and show how this model can be successfully used in natural language applications. In particular, we propose two innovative unsupervised methods for keyword and sentence extraction, and show that the results obtained compare favorably with previously published results on established benchmarks.

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  • Conference on Empirical Methods in Natural Language Processing (EMNLP), 2004, Barcelona, Spain

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  • July 2004

Added to The UNT Digital Library

  • Jan. 31, 2011, 2:01 p.m.

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  • April 28, 2014, 2:22 p.m.

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Mihalcea, Rada, 1974- & Tarau, Paul. TextRank: Bringing Order into Texts, paper, July 2004; [Stroudsburg, Pennsylvania]. (digital.library.unt.edu/ark:/67531/metadc30962/: accessed June 21, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.