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New Technology of Library and Information Service  2010, Vol. 26 Issue (3): 40-46    DOI: 10.11925/infotech.1003-3513.2010.03.07
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Research on Amalgamation Mechanism of FCA and Ontology in Knowledge Modeling
Zhang Yunzhong
(School of Management, Jilin University, Changchun 130022,China)
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For the amalgamation problems of Ontology and FCA in knowledge modeling, the similarities and differences between Ontology and FCA are compared. Then the conditions of amalgamation of Ontology and FCA are analyzed from the perspectives of philosophy, algebraic structure, knowledge processing and knowledge management, and the amalgamation mechanism of Ontology and FCA in the process of knowledge modeling is defined. Finally,the paper comes to the conclusion that Ontology and FCA can be combined on eight idiographic aspects in the process of knowledge modeling, which may offer a wide view for the amalgamation of Ontology and FCA in the field of knowledge modeling.

Key wordsFCA      Ontology      Knowledge modeling      Amalgamation mechanism     
Received: 08 January 2010      Published: 25 March 2010


Corresponding Authors: Zhang Yunzhong     E-mail:
About author:: Zhang Yunzhong

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Zhang Yunzhong. Research on Amalgamation Mechanism of FCA and Ontology in Knowledge Modeling. New Technology of Library and Information Service, 2010, 26(3): 40-46.

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[1] 毕强,滕广青. 国外信息资源管理研究进展及热点分析——基于IRMJ和JASIS的分析[J].中国图书馆学报,2009,35(9):80-90.
[2] Cimiano P. Conceptual Knowledge Processing with Formal Concept Analysis and Ontologies[EB/OL]. [2010-01-15].
[3] Haav H M. A Semi-automatic Method to Ontology Design by Using FCA[EB/OL]. [2010-01-15].
[4] Obitko M,Snasel V, Smid J. Ontology Design with Formal Concept Analysis[EB/OL]. [2010-01-15].
[5] Stumme G, Maedche A. FCA-merge : Bottom-up Merging of Ontologies [EB/OL]. [2010-01-15].
[6] Ganter B, Stumme G.Creation and Merging of Ontology Top-levels [EB/OL]. [2010-01-15].
[7] 周文,刘宗田,陈慧琼.FCA与本体融合研究的综述[J].计算机科学,2006,33(2):8-12.
[8] Stumme G. Formal Concept Analysis on Its Way from Mathematics to Computer Science [EB/OL]. [2010-01-15].
[9] 徐国虎,许芳,董慧. 基于语义关系的本体推理规则研究[J].中国图书馆学报,2007,33(5):88-92.
[10] 曹泽文,钱杰,张维明,等.基于FCA的概念相似度计算方法[J]. 模糊系统与数学,2008,22(1):155-162.
[11] 林智超,朱国进. 一种基于FCA的概念相似度算法[J].计算机技术与发展,2008,18(9):112-126.

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