Abstract
Knowledge graphs (KGs) are a key ingredient for searching, browsing and knowledge discovery activities. Motivated by the need to harness knowledge available in a variety of KGs, we face the following two problems. First, given a pair of entities defined in some KG, find an explanation of their relatedness. We formalize the notion of relatedness explanation and introduce different criteria to build explanations based on information-theory, diversity and their combinations. Second, given a pair of entities, find other (pairs of) entities sharing a similar relatedness perspective. We describe an implementation of our ideas in a tool, called RECAP, which is based on RDF and SPARQL. We provide an evaluation of RECAP and a comparison with related systems on real-world data.
Part of this work was done while the author was working at the WeST institute, University of Koblenz-Landau, Germany. This work was partially supported by the EU Framework Programme for Research and Innovation under grant agreement no. 611242 (SENSE4US) and by the Cyber Security Technological District financed by the Italian Ministry of Education, University and Research.
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Pirrò, G. (2015). Explaining and Suggesting Relatedness in Knowledge Graphs. In: Arenas, M., et al. The Semantic Web - ISWC 2015. ISWC 2015. Lecture Notes in Computer Science(), vol 9366. Springer, Cham. https://doi.org/10.1007/978-3-319-25007-6_36
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DOI: https://doi.org/10.1007/978-3-319-25007-6_36
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