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Titlebook: Intelligent Information Processing IV; 5th IFIP Internation Zhongzhi Shi,E. Mercier-Laurent,D. Leake Conference proceedings 2008 IFIP Inter

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Ke Gao,Shouxun Lin,Yongdong Zhang,Sheng Tangnschaften behaupten regelmäßig die Überlegenheit des US-amerikanischen Hochschulsystems gegenüber dem deutschen. In den seltensten Fällen basieren solche Aussagen auf gesicherten, mit wissenschaftlichen Methoden gewonnenen Erkenntnissen..Auf der Basis organisationsökonomischer Überlegungen und empir
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Conference proceedings 2008owledge pieces” as rather universal objects that should fit to multi-purpose a- ing systems. According to great number of information system’s tasks, knowledge representation is more or less detailed (e.g. some level of its granularity is - sumed). The main goal of this paper is to present chosen as
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1868-4238 cation.The contributors in this volume are world-renowned exKnowledge existing in modern information systems usually comes from many sources and is mapped in many ways. There is a real need for representing “knowledge pieces” as rather universal objects that should fit to multi-purpose a- ing system
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ER2OWL: Generating OWL Ontology from ER Diagrams in upgrading the structured analysis and design artifact ERD, to components of semantic web. Moreover our transformation tool, ER2OWL, reduces the cost and time for building OWL ontologies with the reuse of existing entity relationship models.
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Fuzzy Ontology Models Based on Fuzzy Linguistic Variable for Knowledge Management and Information Re the semantic query expansion in SeRQL is constructed by semantic relations between fuzzy concepts. The application shows that these models can overcome the localization of other fuzzy ontology models, and this research facilitates the fuzzy knowledge sharing and semantic retrieval on the Semantic Web.
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A Context Model for Service Composition Based on Dynamic Description Logicder the context logic. The reasoning results finally can be used to discovery and compose services intelligently. We evaluate this model on a simple, yet realistic example, and the results show that our context model provides a practical solution.
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A Modified Clustering Method with Fuzzy Antsd on Schockaert’s algorithm. This algorithm can be accelerated by the use of parallel ants, global memory banks and density-based ‘look ahead’ method. Experimental results show that this algorithm is more efficient to other ant clustering methods.
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