Agent Intelligence Through Data Mining

Andreas L. Symeonidis

ISBN 10: 0387243526 / ISBN 13: 9780387243528

Editore: Springer-Verlag New York Inc., 2005

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Dati bibliografici

• Titolo: Agent Intelligence Through Data Mining
• Editore: Springer-Verlag New York Inc.
• Data di pubblicazione: 2005
• Lingua: Inglese
• ISBN 10: 0387243526
• ISBN 13: 9780387243528
• Rilegatura: Hardback
• Condizione: New

Descrizione articolo

Riassunto

Knowledge, hidden in voluminous data repositories routinely created and maintained by today’s applications, can be extracted by data mining.

Dalla quarta di copertina

AGENT INTELLIGENCE THROUGH DATA MINING offers a self-contained overview of a relatively young but important area of research: the intersection of agent technology and data mining. This intersection leads to considerable advancements in the area of information technologies, drawing the increasing attention of both research and industrial communities. It can take two forms: a) the more mundane use of intelligent agents for improved data mining and; b) the use of data mining for smarter, more efficient agents. The second approach is the main focus of this volume.

Knowledge, routinely created and maintained by today’s applications, is hidden in voluminous data repositories that can be extracted by data mining. The next step is to transform this discovered knowledge into the inference mechanisms or simply the behavior of agents and multi-agent systems. AGENT INTELLIGENCE THROUGH DATA MINING addresses this issue, as well as the arguable challenge of generating intelligence from data while transferring it to a separate, possibly autonomous, software entity. Following a brief review of data mining and agent technology fields, this book presents a methodology for developing multi-agent systems, describes available open-source tools to support this process, and demonstrates the application of the methodology on three different cases.

AGENT INTELLIGENCE THROUGH DATA MINING is designed for a professional audience composed of researchers and practitioners in industry. This volume is also suitable for graduate-level students in computer science.