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 UNT College of Engineering to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 151 times , with 5 in the last month . More information about this paper can be viewed below.

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UNT College of Engineering

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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Description

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.

Physical Description

9 p.

Source

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

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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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  • May 2009

Added to The UNT Digital Library

  • 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]. (digital.library.unt.edu/ark:/67531/metadc31022/: accessed October 22, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.