Abstract
Currently, Data mining is applied in various domains. Many data science researchers are confused on which algorithms are suitable for the context. Hundreds of the operators/algorithms are combined within complex data mining workflows. A data mining assistant can significantly improve the efficiency of workflow construction. In our previous work, we constructed data mining ontologies based on “semantic meta mining” to support the selection of algorithms and operators for solving data mining tasks. But the use of such ontologies is still unfriendly. Strict query syntax still plagues many users. This paper proposes an interactive interface based on the reasoning mechanism to help users generate queries and build suitable data mining workflows.
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Acknowledgments
«The paper was prepared in Saint- Petersburg Electrotechnical University (LETI), and is supported by the Agreement № 075–11-2019–053 dated 20.11.2019 (Ministry of Science and Higher Education of the Russian Federation, in accordance with the Decree of the Government of the Russian Federation of April 9, 2010 No. 218), project «Creation of a domestic high-tech production of vehicle security systems based on a control mechanism and intelligent sensors, including millimeter radars in the 76–77 GHz range»
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Tianxing, M., Lebedev, S., Vodyaho, A., Zhukova, N., Shichkina, Y.A. (2021). Ontology-Based Data Mining Workflow Construction. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12956. Springer, Cham. https://doi.org/10.1007/978-3-030-87010-2_31
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