The Borda Social Choice Movie Recommender

Abstract

In this demo paper we present a recommender system, which exploits the Borda social choice voting rule for clustering recommendations in order to produce comprehensible results for a user. Considering existing clustering techniques like k-means, the overhead of normalizing and preparing the preferred user data is dropped. In our demo showcase we facilitate a comparison of our clustering approach to the well known k-means++ with traditional distance measures.