Autonomous intelligent systems : agents and data mining : international workshop, AIS-ADM 2005, St. Petersburg, Russia, June 6-8, 2005 : proceedings

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Bibliographic Information

Autonomous intelligent systems : agents and data mining : international workshop, AIS-ADM 2005, St. Petersburg, Russia, June 6-8, 2005 : proceedings

Vladimir Gorodetsky, Jiming Liu, Victor A. Skormin (eds.)

(Lecture notes in computer science, 3505 . Lecture notes in artificial intelligence)

Springer, c2005

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Includes bibliographical references and index

Description and Table of Contents

Description

This volume contains the papers presented at the International Workshop "Autonomous Intelligent Systems: Agents and Data Mining" (AIS-ADM 2005) held in St. Petersburg, Russia, during June 6-8, 2005. The workshop was - ganized by the St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences (SPIIRAS) in cooperation with Binghamton U- versity (SUNY, USA) and the Web Intelligence Consortium. Autonomous Intelligent Systems (AIS) constitute an emerging class of int- ligent information systems integrating recent advances in various technologies of Arti?cial Intelligence. Modern AIS incorporate multi-agent and data mining systemsprovidinganewdimensionforfurtherprogressinintelligentinformation technology. AIS-ADM 2005 provided an international forum to multi-agent and data mining researchers. A total of 29 papers from 15 countries relating to various aspects of both theory and applications of multi-agent systems, data mining and their joint area were submitted to AIS-ADM 2005. Out of them 17 were selected as regular presentations. Three technical sessions were organized, namely: In- gration of Multi-agent and Data Mining Techniques; Ontology Issues and Web Mining; and Applications and Case Studies of the Integrated Technology. The panel discussion was devoted to the mutual enrichment and challenging pr- lems emerging in the joint area of research. The AIS-ADM 2005 program was enriched by six distinguished invited speakers: Nick Jennings, Chengqi Zhang, Mircea Negoita, Pericles Mitkas, Hai Zhuge and Leonid Perlovsky.

Table of Contents

Invited Papers.- Negotiation Technologies.- Knowledge Discovery for Training Intelligent Agents: Methodology, Tools and Applications.- Artificial Immune Systems-An Emergent Technology for Autonomous Intelligent Systems and Data Mining.- Evolving Agents: Communication and Cognition.- Agents and Data Mining: Mutual Enhancement by Integration.- Soft-Device Inheritance in the Knowledge Grid.- Agent Based Data Mining Issues.- Towards the Adaptive Organization: Formation and Conservative Reconfiguration of Agents Coalitions.- A Cooperative Multi-agent Data Mining Model and Its Application to Medical Data on Diabetes.- Technology of Agent-Based Decision Making System Development.- An Architecture for Distributed Agent-Based Data Preprocessing.- Meta-reasoning Methods for Agent's Intention Modelling.- Execution Engine of Meta-learning System for KDD in Multi-agent Environment.- A Methodology for Predicting Agent Behavior by the Use of Data Mining Techniques.- Ontology and Web Mining.- Topic-Specific Text Filtering Based on Multiple Reducts.- Parallel Algorithm for Mining Frequent Closed Sequences.- Decision Trees Capacity and Probability of Misclassification.- Querying Dynamic and Context-Sensitive Metadata in Semantic Web.- Ontology Issue in Multi-agent Distributed Learning.- Ontology-Based Users and Requests Clustering in Customer Service Management System.- Multi-agent Approach for Community Clustering Based on Individual Ontology Annotations.- Applications and Case Studies.- Effective Discovery of Intrusion Protection Strategies.- Integrating Knowledge Through Cooperative Negotiation - A Case Study in Bioinformatics.- Data Mining Techniques for RoboCup Soccer Agents.

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Details
  • NCID
    BA72579002
  • ISBN
    • 3540261648
  • Country Code
    gw
  • Title Language Code
    eng
  • Text Language Code
    eng
  • Place of Publication
    Berlin
  • Pages/Volumes
    xiii, 301 p.
  • Size
    24 cm
  • Parent Bibliography ID
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