Data Mining and Multi-agent Integration

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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 mining Mining temporal patterns to improve agents behavior Information enrichment through recommendation sharing Automatic web data extraction based on genetic algorithms and regular expressions A multiagent learning paradigm for medical data mining diagnostic workbench A multiagent data mining framework Streaming data in complex uncertain environments Large data clustering A multiagent, multi-objective clustering algorithm Interactive web environment for psychometric diagnostics Anomalies detection on distributed firewalls using data mining techniques Automated reasoning for distributed and multiple source of data Video contents identification Data 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.