Abstract
The advent of machine learning has revolutionized how we interpret data and information. In this process, ontology is crucial since it defines the relationships between the data elements. On the other hand, machine learning may be helpful in ontology engineering by automatically generating ontologies from data. This paper explores how ontologies can be utilized in machine learning to improve algorithms’ accuracy and how machine learning can facilitate the ontology engineering process.
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Zemmouchi-Ghomari, L. (2023). Ontology and Machine Learning: A Two-Way Street to Improved Knowledge Representation and Algorithm Accuracy. In: Yadav, A., Nanda, S.J., Lim, MH. (eds) Proceedings of International Conference on Paradigms of Communication, Computing and Data Analytics. PCCDA 2023. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-4626-6_15
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DOI: https://doi.org/10.1007/978-981-99-4626-6_15
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