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Attributes Reduction on SE-ISI Concept Lattice for an Incomplete Context Using Object Ranking

Author

Listed:
  • B. Srirekha

    (Department of Mathematics, SRM Institute of Science, Technology-Ramapuram Campus, Chennai 600 089, India)

  • Shakeela Sathish

    (Department of Mathematics, SRM Institute of Science, Technology-Ramapuram Campus, Chennai 600 089, India)

  • R. Narmada Devi

    (Department of Mathematics, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Avadi, Chennai 600 062, India)

  • Miroslav Mahdal

    (Department of Control Systems and Instrumentation, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava, 17. Listopadu 2172/15, 70800 Ostrava, Czech Republic)

  • Robert Cep

    (Department of Machining, Assembly and Engineering Metrology, Faculty of Mechanical Engineering, VSB-Technical University of Ostrava, 17. Listopadu 2172/15, 70800 Ostrava, Czech Republic)

  • K. Elavarasan

    (Department of Mathematics, Velammal Engineering College, Chennai 600 066, India)

Abstract

The formal concept of lattice plays a vital role in knowledge discovery. Reduction of the attribute has many applications in machine learning technology and data mining fields. In this paper, we introduce an object ranking concept to define a consistency set and the reduction of the attributes by structural features. An incomplete information system works on the three-way concepts using the SE-ISI Context. The granular was emphasized with join (meet) irreducible sets using the object ranking concepts. A dual operator is defined based on the object ranking concepts and its properties and conditions are verified. Hence, this elaborates on the four kinds of reduction of the attributes. The ordered pairs give the knowledge of the attributes that deal with the interval set of both the approximation of rough set theory concerning the objects. Therefore, the relationship between four kinds of reduction of the attribute was appropriate to access the consistency set using the object ranking concepts by some of the theorems and examples.

Suggested Citation

  • B. Srirekha & Shakeela Sathish & R. Narmada Devi & Miroslav Mahdal & Robert Cep & K. Elavarasan, 2023. "Attributes Reduction on SE-ISI Concept Lattice for an Incomplete Context Using Object Ranking," Mathematics, MDPI, vol. 11(7), pages 1-17, March.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:7:p:1585-:d:1106765
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    References listed on IDEAS

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    1. Huilai Zhi & Hao Chao, 2018. "Three-Way Concept Analysis for Incomplete Formal Contexts," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-11, September.
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    Cited by:

    1. Baohua Liang & Erli Jin & Liangfen Wei & Rongyao Hu, 2024. "Knowledge Granularity Attribute Reduction Algorithm for Incomplete Systems in a Clustering Context," Mathematics, MDPI, vol. 12(2), pages 1-25, January.

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