Automatic fuzzy ontology generation for semantic Web

Author

Tho, Quan Thanh ; Hui, Siu Cheung ; Fong, A.C.M. ; Cao, Tru Hoang

Author_Institution

Sch. of Comput. Eng., Nanyang Technol. Univ.

Volume

18

Issue

6

fYear

2006

fDate

6/1/2006 12:00:00 AM

Firstpage

842

Lastpage

856

Abstract

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

Keywords

data analysis; fuzzy logic; fuzzy reasoning; ontologies (artificial intelligence); semantic Web; uncertainty handling; automatic fuzzy ontology generation; concept hierarchy generation; fuzzy formal concept analysis; fuzzy logic; fuzzy-based technique; semantic Web; Data mining; Databases; Fuzzy logic; Knowledge representation; OWL; Ontologies; Search engines; Semantic Web; Uncertainty; Web services; "fuzzy; ” probabilistic; Intelligent Web services and semantic Web; concept learning.; knowledge representation formalisms and methods; ontology design; uncertainty;

fLanguage

English

Journal_Title

Knowledge and Data Engineering, IEEE Transactions on

Publisher

ieee

ISSN

1041-4347

Type

jour

DOI

10.1109/TKDE.2006.87

Filename

1626237