Hyperbolic Geometry Embedding for Complex Ontology Matching
Procedia Computer Science, ISSN: 1877-0509, Vol: 246, Issue: C, Page: 3512-3521
2024
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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Article Description
Complex matching ontology involves measuring the distance between ontological elements. The objective of complex matching ontology is to locate semantically equivalent concepts in two ontologies. The main focus of current complex matching methods is on capturing features related to terminological, structural, and contextual semantics in ontologies. The features of based techniques are intensive but also neglect the hidden semantic relations in ontologies. In this study, we introduce a complex matching ontology model based on hyperbolic geometry embedding. We examine the Hyperbolic geometry embedding for measuring similarity between ontologies, and discovering complex matchings between elements. Our experiments with the Ontology Alignment Evaluation Initiative (OAEI) achieved competitive results compared to the leading systems.
Bibliographic Details
Elsevier BV
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