Service-Oriented Distributed Knowledge Discovery

Domenico Talia, Paolo Trunfio

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October 5, 2012 by Chapman and Hall/CRC
Reference - 230 Pages - 96 B/W Illustrations
ISBN 9781439875315 - CAT# K13494
Series: Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

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Features

  • Introduces parallel and distributed data mining concepts and architectures
  • Describes web and grid technologies for distributed knowledge discovery
  • Explains how to design service-oriented data mining applications
  • Includes a study of workflow formalisms for modeling distributed knowledge discovery applications
  • Presents open source frameworks for developing service-oriented KDD applications, with the open source software available on the authors' website

Summary

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.

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.

Highlighting the latest achievements in the field, the book gives many examples of the state of the art in service-oriented knowledge discovery. Both novices and more seasoned researchers will learn useful concepts related to distributed data mining and service-oriented data analysis. Developers will also gain insight on how to successfully use service-oriented knowledge discovery in databases (KDD) frameworks.