Literatures Supply Chain Knowledge Representation and Reasoning Based on Ontology Theory
Sun Wandong1 Yue Jun2,3 Zhang Jing4
1(Department of Student Work，Ludong University, Yantai 264025, China) 2(College of Management, Ludong University, Yantai 264025,China) 3(College of Information and Electrical Engineering, China Agricultural University,Beijing 100083,China) 4(Ludong University Library, Yantai 264025,China)
Knowledge representation and matching-reasoning are two key steps for a semantic knowledge management system. In order to realize the semantic management of literatures supply chain knowledge, the authors put forward the literatures supply chain knowledge Ontology model and formalize the model using RDF (Resource Description Framework) and advanced Voronoi diagram. The authors setup the qualitative reasoning rules based on the RDF formalized model and put forward the quantitative reasoning arithmetic based on the advanced Voronoi diagram formalized model. The experiments show the reasoning rules and arithmetic based on the formalized model could get rational results in literatures supply chain knowledge management.
孙万东,岳峻,张晶 . 基于本体理论的文献供应链知识表示及推理[J]. 现代图书情报技术, 2007, 2(12): 34-38.
Sun Wandong,Yue Jun,Zhang Jing. Literatures Supply Chain Knowledge Representation and Reasoning Based on Ontology Theory. New Technology of Library and Information Service, 2007, 2(12): 34-38.
［1］ 唐卫宁，徐福缘.基于本体和语义Web服务的供应链知识集成［J］.计算机工程，2006(12)：167-169.
［2］ 田方斌.基于图书供应链的营销渠道管理［J］.图书情报知识，2004(2)：88-90.
［3］ Neches R, Fikes R E, Gruber T R, et al. Enabling Technology for Knowledge Sharing［J］. AI Magazine, 1991, 12(3): 36-56.
［4］ Studer R, Benjamins V R, Fensel D. Knowledge Engineering, Principles and Methods［J］. Data and Knowledge Engineering, 1998, 25(122): 161-197.
［5］ Lenat D, Guha R V. Building Large Knowledge-based Systems: Representation and Inference in the CYC Project［M］.Addison-Wesley， 1990.
［6］ Gruninger M, Fox M S. The Logic of Enterprise Modelling［M］. In:J Brown, D O’Sullivan, Editors, Reengineering the Enterprise, 1995.
［7］ Uschold M, King M, Moralee S, et al. The Enterprise Ontology［J］. The Knowledge Engineering Review, 1998,13(1):31-89.
［8］ Schreiber G, Wielinga B, Jansweijer W. The Kactus View on the ‘o’ word［M］. Workshop on Basic Ontological Issues in Knowledge Sharing: International Joint Conference on Aritificial Intelligence, 1995.
［9］ LiJun Zhu, Lan Tao, Hui Liu. Calculation of the Concept Similarity in Domain Ontology［J］. Journal of South China University of Technology. 2004(32):147-150.
［10］ Budanisky A, Hirst G. Semantic Distance in WordNet:An Experimental,Application-oriented Evaluation of Five Measures［C］.In:Workshop on WordNet and Other Lexical Resources,Second Meeting of the North American Chapter of the Association for Computational Linguistics, Pittsburgh, USA,2001.
［11］ Genest D, Chein M. An Experiment in Document Retrieval Using Conceptual Graphs. Conceptual structures: Fulfilling Peirce’s Dream［R］. Lecture Notes in Artificial Intelligence. August, 1997:1257.
［12］ Myaeng, Sung H. Conceptual Graph Matching as a Plausible Inference Technique for Text Retrieval［C］. In:Proc. of the 5th Conceptual Structures Workshop, Held in Conjunction with AAAI-90, Bosto, 1990.
