Foundations of Intelligent Systems

1. Front Matter

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2. Invited Papers

   1. New Challenges in the World Wide Wisdom Web (W4) Research

      • Jiming Liu

      Pages 1-6

   2. Grounding to the Real World – Architecture for Ubiquitous Computing –

      • Hideyuki Nakashima

      Pages 7-11

   3. Data Mining: Fast Algorithms vs. Fast Results

      • Raghu Ramakrishnan

      Pages 12-13

   4. Knowledge Discovery Services and Tools on Grids

      • Domenico Talia

      Pages 14-23

3. Regular Papers

   1. 1A Knowledge Discovery and Data Mining (1)

      1. Space Decomposition in Data Mining: A Clustering Approach

         • Lior Rokach, Oded Maimon, Inbal Lavi

         Pages 24-31

      2. Time Series Rule Discovery: Tough, Not Meaningless

         • Zbigniew R. Struzik

         Pages 32-39

      3. Mining Diagnostic Rules with Taxonomy from Medical Databases

         • Shusaku Tsumoto

         Pages 40-48

      4. Comparing Simplification Methods for Model Trees with Regression and Splitting Nodes

         • Michelangelo Ceci, Annalisa Appice, Donato Malerba

         Pages 49-56

      5. Goodness-of-Fit Measures for Induction Trees

         • Gilbert Ritschard, Djamel A. Zighed

         Pages 57-64

   2. 1B Knowledge Representation and Integration

      1. PDL with Maximum Consistency Monitors

         • Elisa Bertino, Alessandra Mileo, Alessandro Provetti

         Pages 65-74

      2. Comparing and Merging Ontologies: A Concept Type Hierarchy Approach

         • Dan Corbett

         Pages 75-82

      3. Integrating Information under Lattice Structure

         • V. Phan-Luong, T. TPham, R. Jeansoulin

         Pages 83-87

      4. Functional Ontology for Intelligent Instruments

         • Richard Dapoigny, Eric Benoit, Laurent Foulloy

         Pages 88-92

      5. Constructing an Ontology Based on Hub Words

         • Sang Ok Koo, Soo Yeon Lim, Sang Jo Lee

         Pages 93-97

   3. 2A Intelligent Information Systems (1)

      1. Integration of Heterogeneous, Imprecise and Incomplete Data: An Application to the Microbiological Risk Assessment

         • Patrice Buche, Ollivier Haemmerle, Rallou Thomopoulos

         Pages 98-107

      2. Intelligent Protein 3D Structure Retrieval System

         • Yiqiang Chen, Wen Gao, Lijuan Duan, Xiang Chen, Charles X. Ling

         Pages 108-115

      3. Cognitive Vision Systems in Medical Applications

         • Marek R. Ogiela, Ryszard Tadeusiewicz

         Pages 116-123

      4. An Automated School Timetabling System Using Hybrid Intelligent Techniques

         • Alvin C. M. Kwan, Ken C. K. Chung, Kammy K. K. Yip, Vincent Tam

         Pages 124-134

      5. Representing Audio Data by FS-Trees and Adaptable TV-Trees

         • Alicja A. Wieczorkowska, Zbigniew W. Raś, Li-Shiang Tsay

         Pages 135-142

This volume contains the papers selected for presentation at the 14th International Symposium on Methodologies for Intelligent Systems, ISMIS 2003, held in Maebashi City, Japan, 28–31 October, 2003. The symposium was organized by the Maebashi Institute of Technology in co-operation with the Japanese Society for Artificial Intelligence. It was sponsored by the Maebashi Institute of Technology, Maebashi Convention Bureau, Maebashi City Government, Gunma Prefecture Government, US AFOSR/AOARD, the Web Intelligence Consortium (Japan), Gunma Information Service Industry Association, and Ryomo Systems Co., Ltd. ISMIS is a conference series that was started in 1986 in Knoxville, Tennessee. Since then it has been held in Charlotte (North Carolina), Knoxville (Tennessee), Turin (Italy), Trondheim (Norway), Warsaw (Poland), Zakopane (Poland), and Lyon (France). The program committee selected the following major areas for ISMIS 2003: active media human-computer interaction, autonomic and evolutionary computation, intelligent agent technology, intelligent information retrieval, intelligent information systems, knowledge representation and integration, knowledge discovery and data mining, logic for artificial intelligence, soft computing, and Web intelligence.

• Automat
• artificial intelligence
• data mining
• evolution
• evolutionary computation
• information system
• intelligent systems
• knowledge
• knowledge discovery
• knowledge representation
• logic
• multimedia
• programming

• The International WIC Institute, Beijing University of Technology, China

  Ning Zhong

• Department of Computer Science, University of North Carolina, Charlotte, USA

  Zbigniew W. Raś

• Shimane University, Shimane, Japan

  Shusaku Tsumoto

• Department of Informatics, Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan

  Einoshin Suzuki

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