Intelligent Information Systems 2001

Proceedings of the International Symposium “Intelligent Information Systems X”, June 18–22, 2001, Zakopane, Poland

ISBN: 978-3-7908-1407-1 (Print) 978-3-7908-1813-0 (Online)

Table of contents (25 chapters)

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  1. Front Matter

    Pages I-XII

  2. Rule and Decision Tree Learning

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      Pages 1-12

      Identification of Rules for Brain Metastases and Survival Time Prediction for Small Cell Lung Cancer Patients

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      Pages 13-29

      The Development of the AQ20 Learning System and Initial Experiments

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      Pages 31-41

      Discovering Multi-head Attributional Rules in Large Databases

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      Pages 43-55

      Melanoma Prediction Using k-Nearest Neighbor and LEM2 Algorithms

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      Pages 57-66

      Technologies for Sound Database Indexing: Musical Instrument Classification Methods

  3. Unsupervised Learning

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      Pages 67-74

      Significance Testing in the Grade Correspondence Analysis

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      Pages 75-85

      Ensembles of Similarity-Based Models

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      Pages 87-95

      Regression — Yet Another Clustering Method

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      Pages 97-110

      Taxonomy Building: Cases or Attributes ?

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      Pages 111-120

      Using Grade Correspondence Analysis to Merge Populations and Detect Latent Orders

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      Pages 121-131

      Mining the Preference Relations and Preference Graphs

  4. Biologically Motivated Methods

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      Pages 133-142

      Multi-Dimensional Gaussian and Cauchy Mutations

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      Pages 143-154

      Statistical Genetic Algorithms

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      Pages 155-166

      Cellular Automata Approach to Scheduling Problem in Case of Modifications of a Program Graph

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      Pages 167-178

      Multimodal Optimization with Artificial Immune Systems

  5. Learning and Reasoning Under Uncertainty

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      Pages 179-193

      Bayesian Network Mining System

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      Pages 195-208

      Intelligent Techniques in Stock Analysis

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      Pages 209-220

      Models of Multiple Response Independence

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      Pages 221-226

      The Role of Support and Confidence in Collaborative Query Answering

  6. Logical Foundations of AI

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      Pages 227-237

      Criteria and Functions for Expert Information Representation Choice

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