Talia D., Trunfio P. Service-Oriented Distributed Knowledge Discovery

CRC Press, 2013. — 225 p.Data analysis techniques and services are needed to mine the massive amount of data available and to extract useful knowledge from it. The service-oriented architecture (SOA) is used today as a model to develop software systems as a collection of services that are units of functionality and are interoperable in an open programming scenario. Service-oriented architectures can offer tools, techniques, and environments to support analysis, inference, and discovery processes over large data repositories available in many scientific and business areas. Knowledge discovery services, based on the availability of huge operation and application data and on the exploitation of data mining techniques, support and enable large-scale knowledge discovery applications on service-oriented architectures such as Web servers, Grids, and Cloud computing platforms.
This new approach can be referred to as service-oriented knowledge discovery. It addresses issues related to distributed knowledge discovery algorithms, data services composition, data and knowledge integration, and service-oriented data mining workflows, which provide the main components for extracting useful knowledge from the often unmanageable data volumes available today from many sources. This is done by exploiting data mining and machine learning distributed models and techniques in service-oriented infrastructures.
This book is about distributed knowledge discovery techniques, algorithms, and systems based on the service-oriented paradigm. It introduces service-oriented knowledge discovery techniques, models, and architectures and explains how those can also be implemented through a detailed description of real software systems that are addressed in some chapters. The final part of the book illustrates distributed knowledge discovery applications and discusses the future role of service-oriented knowledge discovery in ubiquitous discovery processes and in large-scale data analytics.
The book covers several key areas in data mining and service-oriented computing: (1) concepts and principles of distributed knowledge discovery and service-oriented data mining; (2) design of services for data analytics; (3) real systems for implementing distributed knowledge discovery applications; (4) mobile data mining models; and (5) future trends in service-oriented data analytics.
The book is for researchers, graduate students, and practitioners in data mining, knowledge discovery, and service-oriented computing fields. Researchers will find some of the latest achievements in the area and many examples of the state-of-the-art in service-oriented knowledge discovery. Both readers who are beginners to the subject and experienced readers in the distributed data mining domain will find topics of interest. Furthermore, graduate students and young researchers will learn useful concepts related to distributed data mining and service-oriented data analysis.Distributed Knowledge Discovery: An Overview
Service-Oriented Computing for Data Analysis
Designing Services for Distributed Knowledge Discovery
Workflows of Services for Data Analysis
Services and Grids: The Knowledge Grid
Mining Tasks as Services: The Case of Weka4WS
How Services Can Support Mobile Data Mining
Knowledge Discovery Applications
Sketching the Future Pervasive Data Services