Open AccessA distributed framework to investigate the entity relatedness problem in large RDF knowledge bases
Author(s) -
Javier Guillot Jiménez,
Luiz André P. Paes Leme,
Yenier Torres Izquierdo,
Angelo Batista Neves Júnior,
Marco A. Casanova
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5753/sbbd.2021.17871
Subject(s) - computer science , rdf , path (computing) , ranking (information retrieval) , knowledge graph , graph , theoretical computer science , knowledge base , information retrieval , entity linking , semantic similarity , data mining , semantic web , artificial intelligence , programming language
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 question can be addressed by implementing a path search strategy, which combines an entity similarity measure, with an expansion limit, to reduce the path search space and a path ranking measure to order the relevant paths between a given pair of entities in the RDF graph. This paper first introduces DCoEPinKB, an in-memory distributed framework that addresses the entity relatedness problem. Then, it presents an evaluation of path search strategies using DCoEPinKB over real data collected from DBpedia. The results provide insights about the performance of the path search strategies.