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Proceedings of SAI Intelligent Systems Conference

IntelliSys 2021: Intelligent Systems and Applications pp 231–238Cite as

The Data Mining Dataset Characterization Ontology

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 295))

Abstract

Data mining technology is applied in kinds of domains in real life. But the diversity of algorithms is bothering many data researchers. Many data mining knowledge bases have been developed, data mining assistants have also been proposed for algorithm selection. However, these studies focus on the description of algorithms, which makes a gap between the raw data and the ontology entities. This paper proposes a dataset characterization ontology, representing dataset characteristics to support the algorithm selection process. An example of dealing with the missing value problem using the proposed ontology is presented.

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Author information

Authors and Affiliations

  1. ITMO University, St. Petersburg, Russia

    Man Tianxing

  2. St. Petersburg State Electrotechnical University “LETI”, St. Petersburg, Russia

    Nataly Zhukova

  3. St. Petersburg Federal Research Center of the Russian Academy of Sciences, St. Petersburg, Russia

    Nataly Zhukova

Authors
  1. Man Tianxing
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  2. Nataly Zhukova
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Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

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© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Tianxing, M., Zhukova, N. (2022). The Data Mining Dataset Characterization Ontology. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2021. Lecture Notes in Networks and Systems, vol 295. Springer, Cham. https://doi.org/10.1007/978-3-030-82196-8_17

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