Ontological Data Mining
Document Type
Book Chapter
Department or Administrative Unit
Computer Science
Publication Date
2-1-2017
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.
Recommended Citation
Vityaev, E., & Kovalerchuk, B. (2017). Ontological Data Mining. In V. Kreinovich (Ed.), Uncertainty Modeling (pp. 277–292). Springer. https://doi.org/10.1007/978-3-319-51052-1_17
Rights
© Springer International Publishing AG 2017
Comments
This article was originally published in Uncertainty Modeling: Dedicated to Professor Boris Kovalerchuk on his Anniversary. The full-text article from the publisher can be found here.
Due to copyright restrictions, this article is not available for free download from ScholarWorks @ CWU.