Semi-metric Networks for Recommender Systems

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 use...

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Bibliographic Details
Published in:2012 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology Vol. 3; pp. 175 - 179
Main Authors: Simas, T., Rocha, L. M.
Format: Conference Proceeding
Language:English
Published: IEEE 01.12.2012
Subjects:
complex networks
fuzzy systems
network theory (graphs)
recommender systems
ISBN:9781467360579, 1467360570
Online Access:Get full text
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Summary: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.
ISBN:9781467360579
1467360570
DOI:10.1109/WI-IAT.2012.245