Summary and Info
Data Mining and Multi-agent Integration presents cutting-edge research, applications and solutions in data mining, and the practical use of innovative information technologies written by leading international researchers in the field. Topics examined include:Integration of multiagent applications and data miningMining temporal patterns to improve agents behaviorInformation enrichment through recommendation sharingAutomatic web data extraction based on genetic algorithms and regular expressionsA multiagent learning paradigm for medical data mining diagnostic workbenchA multiagent data mining frameworkStreaming data in complex uncertain environmentsLarge data clusteringA multiagent, multi-objective clustering algorithmInteractive web environment for psychometric diagnosticsAnomalies detection on distributed firewalls using data mining techniquesAutomated reasoning for distributed and multiple source of dataVideo contents identificationData Mining and Multi-agent Integration is intended for students, researchers, engineers and practitioners in the field, interested in the synergy between agents and data mining. This book is also relevant for readers in related areas such as machine learning, artificial intelligence, intelligent systems, knowledge engineering, human-computer interaction, intelligent information processing, decision support systems, knowledge management, organizational computing, social computing, complex systems, and soft computing.
More About the Author
Longbing Cao (born in 1969) is a Professor in Information Technology at the University of Technology Sydney Australia.
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