Bøger af Domenico Talia

This book constitutes the refereed post-conference proceedings of the First International Conference on Pervasive Knowledge and Collective Intelligence on Web and Social Media, PerSOM 2022, which was held in Messina, Italy, in November 2022. The 9 full papers were carefully reviewed and selected from 35 submissions and present findings of research from the fields of pervasive computing, web, and social media to promote ideas and practices about pervasive knowledge and collective intelligence in this fields. The conference targeted a wide variety of topics including new perspectives in social theories, complex networks, data science, knowledge management, web and social media.

A new approach to distributed large-scale data mining, service-oriented knowledge discovery extracts useful knowledge from todayΓÇÖs 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.

A new approach to distributed large-scale data mining, service-oriented knowledge discovery extracts useful knowledge from 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. It explains how to design services for data analytics, describes real systems for implementing distributed knowledge discovery applications, and explores mobile data mining models.