Knowledge graphs encode semantics that describes resources in terms of several aspects, e.g., neighbors, class hierarchies, or node degrees. Assessing relatedness of knowledge graph entities is crucial for several data-driven tasks, e.g., ranking, clustering, or link discovery. However, existing similarity measures consider aspects in isolation when determining entity relatedness. We address the problem of similarity assessment between knowledge graph entities, and devise GADES. GADES relies on aspect similarities and computes a similarity measure as the combination of these similarity values. We empirically evaluate the accuracy of GADES on knowledge graphs from di fferent domains, e.g., proteins, and news. Experiment results indicate that GADES exhibits higher correlation with gold standards than studied existing approaches. Thus, these results suggest that similarity measures should not consider aspects in isolation, but combinations of them to precisely determine relatedness.
Maria-Esther Vidal is a Full Professor (on-leave) of the Computer Science Department at the Universidad Simón Bolívar, Caracas, Venezuela, and a Visiting Professor and Senior Research Scientist for “Enterprise Information Systems” at the University of Bonn. Her interests include data and knowledge management, knowledge representation and mining, semantic web, and biomedical information management. Maria-Esther has addressed some of the most important challenges in selecting and modeling sources, rewriting queries, cost based optimisation, graph query processing and optimisation, and benchmarks for federated SPARQL query processing. Her proposed strategies have had significant relevant from the early days of information integration in the Web, in the late 90s, and to the emergence of the Semantic Web and SPARQL endpoints. Maria-Esther has published more than 100 peer-reviewed papers in the Semantic Web, Databases, Bioinformatics, and Artificial Intelligence. She is part of various editorial boards (e.g., JWS, JDIQ), and has been co-chair, senior member, and reviewer of several scientific events and journals (e.g., ISWC, AAAI, AMW, WWW, KDE).