On Biclique Connectivity in Bipartite Graphs and Recommendation Systems

Bipartite graphs can be used to model many real-world relationships, with applications in many domains such as medicine and social networks. We present an application of maximal bicliques of bipartite graphs to recommendation systems that makes use of the notion of biclique similarity of a set of vertices in order to recommend items to users in a certain order of preference. Experimental results using real-world datasets that justify our approach are presented.