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Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/11889

Title: Fuzzy Knowledge Management through Knowledge Engineering and Fuzzy Logic
Authors: Lai, Lien-Fu;Huang, Liang-Tsung;Wu, Chao-Chin;Chen, Shi-Shan
Contributors: 資訊工程學系
Keywords: Fuzzy Knowledge Management;Knowledge Engineering;Fuzzy Logic
Date: 2009-10
Issue Date: 2012-07-02T02:26:20Z
Publisher: Chaoyang University of Technology;中華民國人工智慧學會
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.
Relation: The 14th Conference on Artificial Intelligence and Applications (TAAI 2009), Chaoyang University of Technology, Oct. 30-31, 2009: 1-8
Appears in Collections:[Department and Graduate Institute of Computer Science and Information Engineering] Proceedings

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