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OntoDTA: Ontology-Guided Decision Tree Assistance

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  • Khaled Benali

    (Networks, Databases, Computer Science Department, University of Science and Technology of Oran, Algeria, USTO, Oran, Algeria)

  • Sidi Ahmed Rahal

    (Networks, Databases, Computer Science Department, University of Science and Technology of Oran, Algeria, USTO, Oran, Algeria)

Abstract

The effective application of a Decision Tree (DT) process is beset with many difficult and technical decisions about the choice of algorithms, parameters, evaluation, etc. Therefore, we propose assistance by using ontologies for addressing the above-mentioned challenges that face the non-specialist DT miner (person). Ontologies have been used in various research areas such as computer science, including data mining tools. In this paper, we propose the realisation of a domain ontology for DT OntoDTA to empower the non-specialist DT miner throughout the key phases of the DT process. OntoDTA ontology contains the knowledge of DT and provides a common terminology that can be shared and processed by DT miners.

Suggested Citation

  • Khaled Benali & Sidi Ahmed Rahal, 2017. "OntoDTA: Ontology-Guided Decision Tree Assistance," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 1-23, September.
    • Handle: RePEc:wsi:jikmxx:v:16:y:2017:i:03:n:s0219649217500319
    DOI: 10.1142/S0219649217500319
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    References listed on IDEAS

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    1. Longbing Cao & Chengqi Zhang, 2006. "Domain-Driven Data Mining: A Practical Methodology," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 2(4), pages 49-65, October.
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