Data Mining and Multi-agent Integration

1. Agent Driven Data Mining

   1. Integration of Agents and Data Mining in Interactive Web Environment for Psychometric Diagnostics

      • Velibor Ilić

      Pages 251-265

   2. A Multi-Agent Framework for Anomalies Detection on Distributed Firewalls Using Data Mining Techniques

      • Kamel Karoui, Fakher Ben Ftima, Henda Ben Ghezala

      Pages 267-278

   3. Competitive-Cooperative Automated Reasoning from Distributed and Multiple Source of Data

      • Amin Milani Fard

      Pages 279-290

   4. Normative Multi-Agent Enriched Data Mining to Support E-Citizens

      • Stanislaw A. B. Stane, Mariusz Zytniewsk

      Pages 291-304

   5. CV-Muzar - The Virtual Community Environment that Uses Multiagent Systems for Formation of Groups

      • Ana Carolina Bertoletti De Marchi, Márcia Cristina Moraes

      Pages 305-314

   6. Agent based Video Contents Identification and Data Mining Using Watermark based Filtering

      • HeungKyu Lee

      Pages 315-324

   7. Erratum

      • Springer Science+Business Media, LLC

      Pages 329-329

2. Back Matter

   Pages 155-161

   PDF

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.

• AAMAS
• Clustering
• agent-enriched data mining
• algorithm
• algorithms
• automated reasoning
• classification
• currentjm
• data mining
• filtering
• genetic algorithms
• knowledge management
• learning
• multi-agent systems
• regular expressions

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)

• Faculty of Engineering and Information Technology, University of Technology, Sydney, Broadway, Australia

  Longbing Cao

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