A Framework to Compute Entity Relatedness in Large RDF Knowledge Bases

Abstract

The entity relatedness problem refers to the question of exploring a knowledge base, represented as an RDF graph, to discover and understand how two entities are connected. This article addresses such problem by combining distributed RDF path search and ranking strategies in a framework called DCoEPinKB, which helps reduce the overall execution time in large RDF graphs and yet maintains adequate ranking accuracy. The framework allows the implementation of different strategies and enables their comparison. The article also reports experiments with data from DBpedia, which provide insights into the performance of different strategies.