Using Rough Set Theory for Reasoning on Vague Ontologies

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Mustapha Bourahla 1,*

1. Computer Science Department, University of M’Sila, M’Sila, 28000, Algeria

* Corresponding author.


Received: 24 Dec. 2021 / Revised: 1 Feb. 2022 / Accepted: 21 Mar. 2022 / Published: 8 Aug. 2022

Index Terms

Vagueness, Rough Sets, Fuzzy Sets, Description Logics, Fuzzy Description Logics, Ontology Web Language, Automatic Reasoning


Web ontologies can contain vague concepts, which means the knowledge about them is imprecise and then query answering will not possible due to the open world assumption. A concept description can be very exact (crisp concept) or exact (fuzzy concept) if its knowledge is complete, otherwise it is inexact (vague concept) if its knowledge is incomplete. In this paper, we propose a method based on the rough set theory for reasoning on vague ontologies. With this method, the detection of vague concepts will insert into the original ontology new rough vague concepts where their description is defined on approximation spaces to be used by extended Tableau algorithm for automatic reasoning. A prototype of Tableau's extended algorithm is developed and tested on examples where encouraging results are given by this method to demonstrate that unlike other methods, it is possible to answer queries even in the presence of incomplete information.

Cite This Paper

Mustapha Bourahla, "Using Rough Set Theory for Reasoning on Vague Ontologies", International Journal of Intelligent Systems and Applications(IJISA), Vol.14, No.4, pp.21-36, 2022. DOI:10.5815/ijisa.2022.04.03


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