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Ontology is an effective conceptualism commonly used for the Semantic Web. Fuzzy logic can be incorporated to ontology to represent uncertainty information. Typically, fuzzy ontology is generated from a predefined concept hierarchy. However, to construct a concept hierarchy for a certain domain can be a difficult and tedious task. To tackle this problem, this paper proposes the FOGA (Fuzzy Ontology Generation frAmework) for automatic generation of fuzzy ontology on uncertainty information. The FOGA framework comprises the following components: Fuzzy Formal Concept Analysis, Concept Hierarchy Generation, and Fuzzy Ontology Generation. We also discuss approximating reasoning for incremental enrichment of the ontology with new upcoming data. Finally, a fuzzy-based technique for integrating other attributes of database to the ontology is proposed.
Intelligent Web services and semantic Web, ontology design, uncertainty, "fuzzy, ” probabilistic, knowledge representation formalisms and methods, concept learning.

A. Fong, T. H. Cao, S. C. Hui and Q. T. Tho, "Automatic Fuzzy Ontology Generation for Semantic Web," in IEEE Transactions on Knowledge & Data Engineering, vol. 18, no. , pp. 842-856, 2006.
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