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Service-Oriented Distributed Knowledge Discovery

By Domenico Talia, Paolo Trunfio

Chapman and Hall/CRC – 2012 – 230 pages

Series: Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

Purchasing Options:

  • Add to CartHardback: $93.95
    978-1-43-987531-5
    October 5th 2012

Description

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.

Contents

Distributed Knowledge Discovery: An Overview

Knowledge Discovery and Data Mining Concepts

Data Mining Techniques

Parallel Knowledge Discovery

Distributed Knowledge Discovery

Service-Oriented Computing for Data Analysis

Service-Oriented Architecture and Computing

Internet Services: Web, Grids, and Clouds

Service-Oriented Knowledge Discovery

Designing Services for Distributed Knowledge Discovery

A Service-Oriented Layered Approach for Distributed KDD

How KDD Applications Can Be Designed as a Collection of Data Analysis Services

KDD Service-Oriented Applications

Hierarchy of Services for Worldwide KDD

Workflows of Services for Data Analysis

Basic Workflow Concept

Scientific Workflow Management Systems

Workflows for Distributed KDD

Services and Grids: The Knowledge Grid

The Knowledge Grid Architecture

Metadata Management

Workflow Composition Using DIS3GNO

Execution Management

Mining Tasks as Services: The Case of Weka4WS

Enabling Distributed KDD in an Open-Source Toolkit

Weka4WS Architecture

Weka4WS Explorer for Remote Data Mining

Weka4WS Knowledge Flow for Composing Data Mining Services

Execution Management

How Services Can Support Mobile Data Mining

Mobile Data Mining

Mobile Web Services

System for Mobile Data Mining through Web Services

Mobile-to-Mobile (M2M) Data Mining Architecture

Knowledge Discovery Applications

Knowledge Grid Applications

Weka4WS Applications

Web Services Resource Framework (WSRF) Overhead in Distributed Scenarios

Sketching the Future Pervasive Data Services

Service Orientation and Ubiquitous Computing for Data

Toward Future Service-Oriented Infrastructures

Requirements of Future Generation Services

Services for Ubiquitous Computing

Services for Ambient Intelligence and Smart Territories

Conclusive Remarks

Bibliography

Index

Author Bio

Domenico Talia is a professor of computer engineering at the University of Calabria and the director of the Institute of High Performance Computing and Networking of the Italian National Research Council (ICAR-CNR). Dr. Talia is a member of the Association for Computing Machinery and IEEE Computer Society and an editorial board member of the following journals: IEEE Transactions on Computers, Future Generation Computer Systems, International Journal of Web and Grid Services, Journal of Cloud ComputingAdvances, Systems and Applications, Scalable Computing Practice and Experience, International Journal of Next-Generation Computing, Multiagent and Grid Systems: An International Journal, and Web Intelligence and Agent Systems. His research interests include parallel and distributed data mining algorithms, Cloud computing, Grid services, distributed knowledge discovery, peer-to-peer systems, and parallel programming models.

Paolo Trunfio is an assistant professor of computer engineering at the University of Calabria. He has previously worked at the Swedish Institute of Computer Science (SICS) and the Institute of Systems and Computer Science of the Italian National Research Council (ISI-CNR). Dr. Trunfio is a member of the editorial board of ISRN Artificial Intelligence. His research interests include Grid computing, Cloud computing, service-oriented architectures, distributed knowledge discovery, and peer-to-peer systems.

Name: Service-Oriented Distributed Knowledge Discovery (Hardback)Chapman and Hall/CRC 
Description: By Domenico Talia, Paolo Trunfio. 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...
Categories: Data Preparation & Mining, Machine Learning, Computation