1st Edition

Service-Oriented Distributed Knowledge Discovery

By Domenico Talia, Paolo Trunfio Copyright 2013
    230 Pages
    by Chapman & Hall

    230 Pages
    by Chapman & Hall

    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.

    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. Bibliography. Index.


    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.