Abstract
We propose the ontological approach to Data Mining that is based on: (1) the analysis of subject domain ontology, (2) information in data that are interpretable in terms of ontology, and (3) interpretability of Data Mining methods and their results in ontology. Respectively concepts of Data Ontology and Data Mining Method Ontology are introduced. These concepts lead us to a new Data Mining approach—Ontological Data Mining (ODM). ODM uses the information extracted from data which is interpretable in the subject domain ontology instead of raw data. Next we present the theoretical and practical advantages of this approach and the Discovery system that implements this approach. The value of ODM is demonstrated by solutions of the tasks from the areas of financial forecasting, bioinformatics and medicine.
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Acknowledgements
The work has been supported by the Russian Foundation for Basic Research (grant #15-07-03410-a) and Russian Federation grants (Scientific Schools grant of the President of the Russian Federation) #860.2014.1.
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Vityaev, E., Kovalerchuk, B. (2017). Ontological Data Mining. In: Kreinovich, V. (eds) Uncertainty Modeling. Studies in Computational Intelligence, vol 683. Springer, Cham. https://doi.org/10.1007/978-3-319-51052-1_17
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DOI: https://doi.org/10.1007/978-3-319-51052-1_17
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