Text Mining for Automatic Image Tagging

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This paper introduces several extractive approaches for automatic image tagging, relying exclusively on information mined from texts. Through evaluations on two datasets, the authors show that their methods exceed competitive baselines by a large margin, and compare favorably with the state-of-the-art that uses both textual and image features.

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9 p.

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Leong, Chee Wee; Mihalcea, Rada, 1974- & Hassan, Samer August 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 164 times . 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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This paper introduces several extractive approaches for automatic image tagging, relying exclusively on information mined from texts. Through evaluations on two datasets, the authors show that their methods exceed competitive baselines by a large margin, and compare favorably with the state-of-the-art that uses both textual and image features.

Physical Description

9 p.

Source

  • Twenty-third Annual International Conference on Computational Linguistics (COLING), 2010, Beijing, China

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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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  • August 2010

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  • Jan. 31, 2011, 2:01 p.m.

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  • June 20, 2013, 5:39 p.m.

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Leong, Chee Wee; Mihalcea, Rada, 1974- & Hassan, Samer. Text Mining for Automatic Image Tagging, paper, August 2010; (digital.library.unt.edu/ark:/67531/metadc31028/: accessed September 21, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT College of Engineering.