Using Encyclopedic Knowledge for Automatic Topic Identification

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This paper presents a method for automatic topic identification using an encyclopedic graph derived from Wikipedia. The system is found to exceed the performance of previously proposed machine learning algorithms for topic identification, with an annotation consistency comparable to human annotations.

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9 p.

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Coursey, Kino High; Mihalcea, Rada, 1974- & Moen, William E. May 2009.

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

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This paper presents a method for automatic topic identification using an encyclopedic graph derived from Wikipedia. The system is found to exceed the performance of previously proposed machine learning algorithms for topic identification, with an annotation consistency comparable to human annotations.

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9 p.

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  • Thirteenth Annual Conference on Natural Language Learning (CoNLL), 2009, Boulder, Colorado, United States

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  • May 2009

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  • Jan. 31, 2011, 2:01 p.m.

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  • April 28, 2014, 2:26 p.m.

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Coursey, Kino High; Mihalcea, Rada, 1974- & Moen, William E. Using Encyclopedic Knowledge for Automatic Topic Identification, paper, May 2009; [Stroudsburg, Pennsylvania]. (https://digital.library.unt.edu/ark:/67531/metadc31022/: accessed June 20, 2025), University of North Texas Libraries, UNT Digital Library, https://digital.library.unt.edu; crediting UNT College of Engineering.

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