A distributed framework to investigate the entity relatedness problem in large RDF knowledge bases


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.

Palavras-chave: Entity Relatedness, Similarity Measure, Relationship Path Ranking, Backward Search, Knowledge Base


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GUILLOT JIMÉNEZ, Javier; P. PAES LEME, Luiz André; TORRES IZQUIERDO, Yenier; BATISTA NEVES, Angelo; CASANOVA, Marco A.. A distributed framework to investigate the entity relatedness problem in large RDF knowledge bases. In: SIMPÓSIO BRASILEIRO DE BANCO DE DADOS (SBBD), 36. , 2021, Rio de Janeiro. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2021 . p. 121-132. ISSN 2763-8979. DOI: https://doi.org/10.5753/sbbd.2021.17871.