Ontology theory, management and design

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Ian H. Witten, Eibe Frank

"This book offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. Inside, you'll learn all you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining - including both tried-and-true techniques of the past and Java-based methods at the leading edge of contemporary research. If you're involved at any level in the work of extracting usable knowledge from large collections of data, this clearly written and effectively illustrated book will prove an invaluable resource."--Jacket.

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Gerhard Weiss

This is the first comprehensive introduction to multiagent systems and contemporary distributed artificial intelligence. The book provides detailed coverage of basic topics as well as several closely related ones and is suitable as a textbook. The book can be used for teaching as well as self-study, and it is designed to meet the needs of both researchers and practitioners. In view of the interdisciplinary nature of the field, it will be a useful reference not only for computer scientists and engineers, but for social scientists and management and organization scientists as well.

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Shu-Heng Chen, Paul P. Wang

Due to the ability to handle specific characteristics of economics and finance forecasting problems like e.g. non-linear relationships, behavioral changes, or knowledge-based domain segmentation, we have recently witnessed a phenomenal growth of the application of computational intelligence methodologies in this field. In this volume, Chen and Wang collected not just works on traditional computational intelligence approaches like fuzzy logic, neural networks, and genetic algorithms, but also examples for more recent technologies like e.g. rough sets, support vector machines, wavelets, or ant algorithms. After an introductory chapter with a structural description of all the methodologies, the subsequent parts describe novel applications of these to typical economics and finance problems like business forecasting, currency crisis discrimination, foreign exchange markets, or stock markets behavior.

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Dieter Fensel

Ontologies have been developed and investigated for some time in artificial intelligence to facilitate knowledge sharing and reuse. More recently, the notion of ontologies has attracted attention from fields such as databases, intelligent information integration, cooperative information systems, information retrieval, electronic commerce, enterprise application integration, and knowledge management. This broadened interest in ontologies is based on the feature that they provide a machine-processable semantics of information sources that can be communicated among agents as well as between software artifacts and humans. This feature makes ontologies the backbone technology of the next web generation, i.e., the Semantic Web. Ontologies are currently applied in areas such as knowledge management in large company-wide networks and call centers, and in B2C, B2G, and B2B electronic commerce. In a nutshell, ontologies enable effective and efficient access to heterogeneous and distributed information sources. Given the increasing amount of information available online, this kind of support is becoming more important day by day. The author systematically introduces the notion of ontologies to the non-expert reader and demonstrates in detail how to apply this conceptual framework for improved intranet retrieval of corporate information and knowledge and for enhanced Internet-based electronic commerce. He also describes ontology languages (XML, RDF, and OWL) and ontology tools, and the application of ontologies. In addition to structural improvements, the second edition covers recent developments relating to the Semantic Web, and emerging web-based standard languages.