Integrating Knowledge for Subjectivity Sense Labeling

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This paper discusses integrating knowledge for subjectivity sense labeling.

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9 p.

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Gyamfi, Yaw; Wiebe, Janyce M.; Mihalcea, Rada, 1974- & Akkaya, Cem 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 89 times . More information about this paper can be viewed below.

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This paper discusses integrating knowledge for subjectivity sense labeling.

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9 p.

Notes

Abstract: This paper introduces an integrative approach to automatic word sense subjectivity annotation. We use features that exploit the hierarchical structure and domain information in lexical resources such as WordNet, as well as other types of features that measure the similarity of glosses and the overlap among sets of semantically related words. Integrated in a machine learning framework, the entire set of features is found to give better results than any individual type of feature.

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  • Association for Computational Linguistics. North American Chapter (NAACL) Conference, 2009, Boulder, Colorado, United States

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  • May 2009

Added to The UNT Digital Library

  • Jan. 31, 2011, 2:01 p.m.

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  • March 27, 2014, 12:06 p.m.

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Gyamfi, Yaw; Wiebe, Janyce M.; Mihalcea, Rada, 1974- & Akkaya, Cem. Integrating Knowledge for Subjectivity Sense Labeling, paper, May 2009; (digital.library.unt.edu/ark:/67531/metadc31013/: accessed December 11, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.