Collaborative filtering using electrical resistance network models

Authors:
Jérôme Kunegis;Stephan Schmidt
Affiliations:
DAI-Labor, Technische Universität Berlin, Berlin, Germany;DAI-Labor, Technische Universität Berlin, Berlin, Germany
Venue:
ICDM'07 Proceedings of the 7th industrial conference on Advances in data mining: theoretical aspects and applications
Year:
2007

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Abstract

In a recommender system where users rate items we predict the rating of items users have not rated. We define a rating graph containing users and items as vertices and ratings as weighted edges. We extend the work of [1] that uses the resistance distance on the bipartite rating graph incorporating negative edge weights into the calculation of the resistance distance. This algorithm is then compared to other rating prediction algorithms using data from two rating corpora.