Collaborative Filtering Using Electrical Resistance Network Models

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.

• Type: Conference
• Year: 2007
• Where: INCDM
• Authors: Jérôme Kunegis, Stephan Schmidt
• Keywords: Graph Containing Users, INCDM 2007, Rating Graph, Users Rate Items