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Semi-metric networks for recommender systems

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations

Abstract

Weighted graphs obtained from co-occurrence in user-item relations lead to non-metric topologies. We use this semi-metric behavior to issue recommendations, and discuss its relationship to transitive closure on fuzzy graphs. Finally, we test the performance of this method against other item- and user-based recommender systems on the Movie lens benchmark. We show that including highly semi-metric edges in our recommendation algorithms leads to better recommendations.

Original languageEnglish
Title of host publicationProceedings of the 2012 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Workshops, WI-IAT 2012
Pages175-179
Number of pages5
DOIs
StatePublished - 2012
Event2012 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Workshops, WI-IAT 2012 - Macau, China
Duration: Dec 4 2012Dec 7 2012

Publication series

NameProceedings of the 2012 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Workshops, WI-IAT 2012

Conference

Conference2012 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Workshops, WI-IAT 2012
Country/TerritoryChina
CityMacau
Period12/4/1212/7/12

Keywords

  • complex networks
  • fuzzy systems
  • network theory (graphs)
  • recommender systems

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