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New Technology of Library and Information Service  2007, Vol. 2 Issue (1): 6-9    DOI: 10.11925/infotech.1003-3513.2007.01.02
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Research on Knowledge Collaboration Model Based on Ontology
Jin Xin   Cao Huaihu   Jia Chuanliang
(School of Information, Central University of Finance & Economics, Beijing 100081,China)
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This paper introduces a solution of implementing Ontology into collaboration of heterogeneous information systems, and presents an Ontology-based Knowledge Collaboration Model-OKCM which is the loose coupling model for Web information interoperation. This paper also describes the system architecture of OKCM and introduces the knowledge representation of the Ontology. It also introduces how to implement and maintain the knowledge collaboration based on the OKCM with the typical business collaboration flow of supply chain.

Key wordsKnowledge collaboration      Ontology      Information interoperability     
Received: 16 October 2006      Published: 25 January 2007


Corresponding Authors: Jin Xin     E-mail:
About author:: Jin Xin,Cao Huaihu,Jia Chuanliang

Cite this article:

Jin Xin,Cao Huaihu,Jia Chuanliang . Research on Knowledge Collaboration Model Based on Ontology. New Technology of Library and Information Service, 2007, 2(1): 6-9.

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1史美林,向勇等. 计算机支持的协同工作理论与应用. 北京:电子工业出版社, 2000.200-210
2Fensel D, Horrocks I, Harmelen F V, Decker S, Erdmann M, Klein M. OIL in a NutShell. Proceedings of the 12th European Workshop on  Knowledge Acquisition, Modeling, and Management. Germany:Springer-Verlag, 2000.1-16
3Zhan Cui, Dean Jones and Paul O’Brien. Issues in Ontology-based Information Integration. Proceedings of Seventeenth International Joint Conference on Artificial Intelligence. Seattle, Washington, USA, 2001(8):187-190
4Thomas R. Gruber.Ontolingua: A Mechanism to Support Portable Ontologies. Technical Report. Knowledge Systems Laboratory, Stanford University, Stanford, USA. Jun.8,2006)
5Qiming Chen, Meichun Hsu, Umeshwar Dayal and etc. Multi-Agent Cooperation, Dynamic Workflow and XML for E-Commerce Automation.HP Labs Technical Report( HPL-1999-136). Software Technology Laboratory, Palo Alto, CA, 1999.8
6IBM Web Service Architecture Team. Web Services Architecture Overview-The next stage of evoluton for e-business.http://developer. ibm. Com(Accessed Jun.8,2006)

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