A graph-based meta-approach for tag recommendation

Abstract

In this paper we propose a graph-coarsening approach that aims to speed-up the execution time of graph-based tag recommenders in large-scale folksonomies. A community detection algorithm in multiplex networks is applied for coarsening the hypergraph depicting a folksonomy. Experiments on real datasets show the validity of the approach.