Abstract
This paper deals with the ontology matching problem, and proposes a pattern mining approach that exploits the different correlation and dependencies between the different properties to select the most appropriate features for the matching process. The proposed method first discovers the frequent patterns from the ontology database, and then find out the most relevant features using the patterns derived. To demonstrate the usefulness of the suggested method, several experiments have been carried out on the DBpedia ontology databases. The results show that our proposal outperforms the state-of-the-art ontology matching approaches in terms of both execution time and quality of the matching process.
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Notes
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Code available at https://github.com/YousIA/PMOM.
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Acknowledgment
Youcef Djenouri’s work was carried out at the Norwegian University of Science and Technology (NTNU), funded by a postdoctoral fellowship from the European Research Consortium for Informatics and Mathematics (ERCIM).
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Belhadi, H., Akli-Astouati, K., Djenouri, Y., Lin, J.CW. (2019). Exploring Pattern Mining for Solving the Ontology Matching Problem. In: Welzer, T., et al. New Trends in Databases and Information Systems. ADBIS 2019. Communications in Computer and Information Science, vol 1064. Springer, Cham. https://doi.org/10.1007/978-3-030-30278-8_11
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