RDF approximate queries based on semantic similarity

Abstract

In this paper, we propose a query relaxation approach to handle the problem of empty or too little answers returned from RDF query. We apply RDF entailment to triple patterns in the original query to get more general answers. We propose the notion of semantic similarity degree so that the returned answers are semantically close to the original query. We present how to compute the semantic similarity degree of a relaxed query with respect to the original query. With the semantic similarity degrees, we can choose the relaxed queries that are semantically close to the original query. On this basis, we give the query relaxation algorithm. We verify our approach by experiments. It is shown that our approach of RDF query relaxation based on the semantic similarity degree has some good performances and is feasible.