Fuzzy knowledge management through knowledge engineering and fuzzy logic

Lien-Fu Lai, Liang Tsung Huang, Chao-Chin Wu, Shi Shan Chen

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Knowledge management (KM) facilitates the capture, storage, and dissemination of knowledge using information technology. In this paper, we propose a FKM (Fuzzy Knowledge Management) approach to managing fuzzy knowledge through knowledge engineering and fuzzy logic. First, fuzziness is introduced into CGs (Conceptual Graphs) for constructing fuzzy knowledge models. Fuzzy knowledge models are used to organize and express various types of fuzzy knowledge through fuzzy CGs. Fuzzy inference rules in fuzzy CGs are identified to offer the deduction capability for reasoning about fuzzy knowledge. Second, fuzzy knowledge models can be classified and stored in a hierarchical ontology system. Ontologies serve as the common understanding of fuzzy knowledge and facilitate the finding of specific fuzzy knowledge relevant to a given domain.

Original languageEnglish
Pages (from-to)7-15
Number of pages9
JournalJournal of Convergence Information Technology
Volume5
Issue number3
DOIs
Publication statusPublished - 2010 Jan 1

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Knowledge engineering
Knowledge management
Fuzzy logic
Ontology
Fuzzy inference
Information technology
Computer systems

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Computer Networks and Communications

Cite this

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Fuzzy knowledge management through knowledge engineering and fuzzy logic. / Lai, Lien-Fu; Huang, Liang Tsung; Wu, Chao-Chin; Chen, Shi Shan.

In: Journal of Convergence Information Technology, Vol. 5, No. 3, 01.01.2010, p. 7-15.

Research output: Contribution to journalArticle

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