Data Mining and Multi-agent Integration

to Agents and Data Mining Interaction.- to Agent Mining Interaction and Integration.- Towards the Integration of Multiagent Applications and Data Mining.- Agent-Based Distributed Data Mining: A Survey.- Data Mining Driven Agents.- Exploiting Swarm Behaviour of Simple Agents for Clustering Web Users’ Session Data.- Mining Temporal Patterns to Improve Agents Behavior: Two Case Studies.- A Multi-Agent System for Extracting and Analysing Users’ Interaction in a Collaborative Knowledge Management System.- Towards Information Enrichment through Recommendation Sharing.- A Multiagent-based Intrusion Detection System with the Support of Multi-Class Supervised Classification.- Automatic Web Data Extraction Based on Genetic Algorithms and Regular Expressions.- Establishment and Maintenance of a Knowledge Network by Means of Agents and Implicit Data.- Equipping Intelligent Agents with Commonsense Knowledge acquired from Search Query Logs: Results from an Exploratory Story.- A Multi-Agent Learning Paradigm for Medical Data Mining Diagnostic Workbench.- Agent Driven Data Mining.- The EMADS Extendible Multi-Agent Data Mining Framework.- A Multiagent Approach to Adaptive Continuous Analysis of Streaming Data in Complex Uncertain Environments.- Multiagent Systems for Large Data Clustering.- A Multiagent, Multiobjective Clustering Algorithm.- Integration of Agents and Data Mining in Interactive Web Environment for Psychometric Diagnostics.- A Multi-Agent Framework for Anomalies Detection on Distributed Firewalls Using Data Mining Techniques.- Competitive-Cooperative Automated Reasoning from Distributed and Multiple Source of Data.- Normative Multi-Agent Enriched Data Mining to Support E-Citizens.- CV-Muzar - The Virtual Community Environment that Uses Multiagent Systems for Formationof Groups.- Agent based Video Contents Identification and Data Mining Using Watermark based Filtering.- Erratum.

From the reviews:

“This book promotes the latest methodological, technical, and practical advancements in the use of agents in data mining applications. … chapters include extensive bibliographies. … The book is intended for students, researchers, engineers, and practitioners, in both agent and data mining areas, who are interested in the potential of integrating agents and mining. … interested readers who are willing to make an effort to build on the book’s material will benefit from reading it.” (J. P. E. Hodgson, ACM Computing Reviews, December, 2009)