Combination of evidence in recommendation systems characterized by distance functions

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Recommendation systems for different Document Networks (DN) such as the World Wide Web (WWW), Digitnl Libarries, or Scientific Databases, often make use of distance functions extracted from relationships among documents and between documents and semantic tags. For instance, documents In the WWW are related via a hyperlink network, while documents in bibliographic databases are related by citation and collaboration networks.Furthermore, documents can be related to semantic tags such as keywords used to describe their content, The distance functions computed from these relations establish associative networks among items of the DN, and allow recommendation systems to identify relevant associations for iudividoal ... continued below

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6 p.

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Rocha, L. M. (Luis Mateus) January 1, 2002.

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Recommendation systems for different Document Networks (DN) such as the World Wide Web (WWW), Digitnl Libarries, or Scientific Databases, often make use of distance functions extracted from relationships among documents and between documents and semantic tags. For instance, documents In the WWW are related via a hyperlink network, while documents in bibliographic databases are related by citation and collaboration networks.Furthermore, documents can be related to semantic tags such as keywords used to describe their content, The distance functions computed from these relations establish associative networks among items of the DN, and allow recommendation systems to identify relevant associations for iudividoal users. The process of recommendation can be improved by integrating associative data from different sources. Thus we are presented with a problem of combining evidence (about assochaons between items) from different sonrces characterized by distance functions. In this paper we summarize our work on (1) inferring associations from semi-metric distance functions and (2) combining evidence from different (distance) associative DN.

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6 p.

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  • "Submitted to: 2002 World Congress on Computational Intellgence, 2002 IEEE International Conference on Fuzzy Systems."

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  • Report No.: LA-UR-02-0154
  • Report No.: LA-UR-02-154
  • Grant Number: none
  • Office of Scientific & Technical Information Report Number: 975940
  • Archival Resource Key: ark:/67531/metadc928663

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  • January 1, 2002

Added to The UNT Digital Library

  • Nov. 13, 2016, 7:26 p.m.

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  • Dec. 9, 2016, 10:57 p.m.

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Rocha, L. M. (Luis Mateus). Combination of evidence in recommendation systems characterized by distance functions, article, January 1, 2002; United States. (digital.library.unt.edu/ark:/67531/metadc928663/: accessed November 19, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.