Data Mining and Multi-agent Integration

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. Front Matter....Pages i-xiii Front Matter....Pages 1-1 Introduction to Agent Mining Interaction and Integration....Pages 3-36 Towards the Integration of Multiagent Applications and Data Mining....Pages 37-46 Agent-Based Distributed Data Mining: A Survey....Pages 47-58 Front Matter....Pages 60-60 Exploiting Swarm Behaviour of Simple Agents for Clustering Web Users’ Session Data....Pages 61-75 Mining Temporal Patterns to Improve Agents Behavior: Two Case Studies....Pages 77-92 A Multi-Agent System for Extracting and Analysing Users’ Interaction in a Collaborative Knowledge Management System....Pages 93-102 Towards Information Enrichment through Recommendation Sharing....Pages 103-126 A Multiagent-based Intrusion Detection System with the Support of Multi-Class Supervised Classification....Pages 127-142 Automatic Web Data Extraction Based on Genetic Algorithms and Regular Expressions....Pages 143-154 Establishment and Maintenance of a Knowledge Network by Means of Agents and Implicit Data....Pages 155-166 Equipping Intelligent Agents with Commonsense Knowledge acquired from Search Query Logs: Results from an Exploratory Story....Pages 167-176 A Multi-Agent Learning Paradigm for Medical Data Mining Diagnostic Workbench....Pages 177-186 Front Matter....Pages 188-188 The EMADS Extendible Multi-Agent Data Mining Framework....Pages 189-200 A Multiagent Approach to Adaptive Continuous Analysis of Streaming Data in Complex Uncertain Environments....Pages 201-218 Multiagent Systems for Large Data Clustering....Pages 219-238 A Multiagent, Multiobjective Clustering Algorithm....Pages 239-249 Integration of Agents and Data Mining in Interactive Web Environment for Psychometric Diagnostics....Pages 251-265 A Multi-Agent Framework for Anomalies Detection on Distributed Firewalls Using Data Mining Techniques....Pages 267-278 Competitive-Cooperative Automated Reasoning from Distributed and Multiple Source of Data....Pages 279-290 Normative Multi-Agent Enriched Data Mining to Support E-Citizens....Pages 291-304 Front Matter....Pages 188-188 CV-Muzar - The Virtual Community Environment that Uses Multiagent Systems for Formation of Groups....Pages 305-314 Agent based Video Contents Identification and Data Mining Using Watermark based Filtering....Pages 315-324 Erratum....Pages 329-329 Back Matter....Pages 155-161 Data Mining and Multi agent Integration aims to re?ect state of the art research and development of agent mining interaction and integration (for short, agent min ing). The book was motivated by increasing interest and work in the agents data min ing, and vice versa. The interaction and integration comes about from the intrinsic challenges faced by agent technology and data mining respectively; for instance, multi agent systems face the problem of enhancing agent learning capability, and avoiding the uncertainty of self organization and intelligence emergence. Data min ing, if integrated into agent systems, can greatly enhance the learning skills of agents, and assist agents with predication of future states, thus initiating follow up action or intervention. The data mining community is now struggling with mining distributed, interactive and heterogeneous data sources. Agents can be used to man age such data sources for data access, monitoring, integration, and pattern merging from the infrastructure, gateway, message passing and pattern delivery perspectives. These two examples illustrate the potential of agent mining in handling challenges in respective communities. There is an excellent opportunity to create innovative, dual agent mining interac tion and integration technology, tools and systems which will deliver results in one new technology. Reports on the research and development progress in promoting the synergism of two cutting-edge technologies - agents and data mining. This title presents the methodologies, algorithms and systems that integrate these two technologies