Titlebook: Soft Computing in Ontologies and Semantic Web; Zongmin Ma Book 2006 Springer-Verlag Berlin Heidelberg 2006 Alignment.Bayesian network.Web

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On Some Problems of Decision-Making Under Uncertainty in the Semantic Webrk that considers uncertainty and imprecision as a first-class characteristic. This paper provides an account of some important problems that arise in such flexible account of the Semantic Web, in an attempt to outline a context for further research.

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Book 2006ms, neural networks, rough sets, Bayesian networks, and other probabilistic techniques) in the ontologies and Semantic Web. How components of the Semantic Web (like the RDF, Description Logics, ontologies) can be covered with a soft computing focus is shown. The book aims to provide a single account

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The SP Theory and the Representation and Processing of Knowledgehensibility in the representation of knowledge, an ability to cope with errors and uncertainties in knowledge, and capabilities for ‘intelligent’ processing of knowledge, including probabilistic reasoning, pattern recognition, information retrieval, unsupervised learning, planning and problem solving.

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An Ontology-Based Method for User Model Acquisition and updated by means of an on-line evolutionary algorithm. The approach has been successfully implemented in a module of a knowledge management system which helps the system improve the relevance of responses to user queries.

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BayesOWL: Uncertainty Modeling in Semantic Web Ontologiesn or to achieve semantic interoperability among heterogeneous systems. This chapter presents an on-going research on developing a framework which augments and supplements the semantic web ontology language OWL. for representing and reasoning with uncertainty based on Bayesian networks (BN) [26], and

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