Chapman & Hall/CRC data mining and knowledge discovery series
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
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Includes bibliographical references (p. 193-201) and index
SUMMARY OR ABSTRACT
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A new approach to distributed large-scale data mining, service-oriented knowledge discovery extracts useful knowledge from today's often unmanageable volumes of data by exploiting data mining and machine learning distributed models and techniques in service-oriented infrastructures. Service-Oriented Distributed Knowledge Discovery presents techniques, algorithms, and systems based on the service-oriented paradigm. Through detailed descriptions of real software systems, it shows how the techniques, models, and architectures can be implemented
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Describes Web and Grid technologies for distributed knowledge discovery
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Explains how to design service-oriented data mining applications
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Features
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Gives many examples of the state of the art in service-oriented knowledge discovery applications
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Includes a study of workflow formalisms for modeling distributed knowledge discovery applications
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Introduces parallel and distributed data mining concepts and architectures
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Presents open source frameworks for developing service-oriented knowledge discovery in databases (KDD) applications Book jacket
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The book covers key areas in data mining and: service-oriented computing. It presents the concepts and principles of distributed knowledge discovery and service-oriented data mining. The authors illustrate how to design services for data analytics, describe real systems for implementing distributed knowledge discovery applications, and explore mobile data mining models. They also discuss the future role of service-oriented knowledge discovery in ubiquitous discovery processes and large-scale data analytics