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A comprehensive review of type-2 fuzzy Ontology


Ontologies are not only crucial for extending the traditional web into the Semantic Web but also for developing intelligent applications, by converting the raw data into smart data, through semantic enrichment. However, crisp Ontologies are not able to represent fuzzy knowledge which is often encountered in real-world applications. Fuzzy Ontology introduces fuzzy logical rules in Ontology for representing imprecise domain concepts such as darkness, hotness, thickness, creamy etc. in a machine-readable and interoperable format. The performance of fuzzy Ontology decreases with the increase of fuzziness in the domain knowledge. Type-2 fuzzy Ontologies (T2FO) were introduced to represent the domain knowledge where the concepts are either extremely vague or their vagueness increases gradually. The type-2 fuzzy Ontology domain is continuously expanding and there is a need to provide a comprehensive review incorporating the literature of T2FO development approaches, its applications in different domains, reasoners developed for inferencing on type-2 fuzzy Ontology, and evaluation approaches. To perform a comprehensive survey about the T2FO, we used Google Scholar as the main literature research tool to review papers published between 1998 to 2018. We then summarized the published approaches by comparing their features proposed for T2FO development, reasoning or inference, and evaluation approaches. This paper also identifies the domains wherein the past T2FO has been used to develop real-world applications. We conclude this paper by summarizing the previous work, and by identifying the research gaps for investigators.

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Correspondence to Syed Ahmad Chan Bukhari.

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Qasim, I., Alam, M., Khan, S. et al. A comprehensive review of type-2 fuzzy Ontology. Artif Intell Rev 53, 1187–1206 (2020).

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  • Ontology
  • Fuzzy Ontology
  • Type-2 fuzzy Ontology
  • Fuzzy knowledge