Intelligent Data Engineering and Automated Learning - IDEAL 2006: 7th International Conference, Burgos, Spain, September 20-23, 2006, Proceedings (Lecture Notes in Computer Science, 4224)

Since its establishment in Hong Kong in 1998,the international Intelligent Data Engineering and Automated Learning (IDEAL) conference has become a r- erence for researchers in both theoretical and practical aspects of learning and information processing, data mining, retrieval and management, bioinformatics and bio-inspired models, agents and hybrid systems and ?nancial engineering. The purpose of IDEAL conferences has been to provide a broad and interd- ciplinary forum for scientists, researchers, and practitioners in these areas from around the world. A special feature of IDEAL conferences is cross-disciplinary exchange of ideas in emerging topics and application in these areas. Data ana- sis and engineering and associated learning paradigms are playing increasingly important roles in an increasing number of applications and ?elds. The mul- disciplinary nature of contemporary research is pushing the boundaries and one of the principal aims of the IDEAL conferences is to promote interactions and collaborations across disciplines. This volume of Lecture Notes in Computer Science contains accepted - pers presented at IDEAL 2006 held at the University of Burgos, Spain, during, September 20–23, 2006. The conference received 557 submissions from over 40 countriesaroundtheworld,whichweresubsequentlyrefereedbytheProgramme Committeeandmanyadditionalreviewers.Afterrigorousreview,170top-quality papers were accepted and included in the proceedings. The acceptance rate was only 30%, which ensured an extremely high-quality standard of the conference. The buoyant number of submitted papers is a clear proof of the vitality and increased importance of the ?elds related to IDEAL, and is also an indication of the rising popularity of the IDEAL conferences. Frontmatter Learning and Information Processing On Some of the Neural Mechanisms Underlying Adaptive Behavior On Correlation Measures of Intuitionistic Fuzzy Sets A More Effective Constructive Algorithm for Permutation Flowshop Problem A Fast Algorithm for Relevance Vector Machine Time Series Relevance Determination Through a Topology-Constrained Hidden Markov Model A Fast Data Preprocessing Procedure for Support Vector Regression Classification by Weighting, Similarity and kNN An Improved EM Algorithm for Statistical Segmentation of Brain MRI Process State and Progress Visualization Using Self-Organizing Map Exploiting Spatio--temporal Data for the Multiobjective Optimization of Cellular Automata Models Comparing Support Vector Machines and Feed-forward Neural Networks with Similar Parameters A New Model Selection Method for SVM Speed-Up LOO-CV with SVM Classifier Integration of Strategies Based on Relevance Feedback into a Tool for the Retrieval of Mammographic Images Generalization Performance of Exchange Monte Carlo Method for Normal Mixture Models Evolutionary Design of gdSOFPNN for Modeling and Prediction of NOx Emission Process Upper Bounds for Variational Stochastic Complexities of Bayesian Networks A Neural Stochastic Optimization Framework for Oil Parameter Estimation Bootstrap Prediction Intervals for Nonlinear Time-Series Effectiveness of Considering State Similarity for Reinforcement Learning On the Structural Robustness of Evolutionary Models of Cooperation Prediction of Chaotic Time Series Based on Multi-scale Gaussian Processes Visual Sensitivity Analysis for Artificial Neural Networks Performance of BSDT Decoding Algorithms Based on Locally Damaged Neural Networks K Nearest Sequence Method and Its Application to Churn Prediction Evolutionary Computation Technique Applied to HSPF Model Calibration of a Spanish Watershed Genetic Algorithms and Sensitivity Analysis Applied to Select Inputs of a Multi-Layer Perceptron for the Prediction of Air Pollutant Time-Series Genetic Algorithms for Estimating Longest Path from Inherently Fuzzy Data Acquired with GPS The Topographic Neural Gas A Fast Classification Algorithm Based on Local Models Human Activity Recognition in Videos: A Systematic Approach Application of Artificial Neural Network to Building Compartment Design for Fire Safety A Method of Motion Segmentation Based on Region Shrinking A Family of Novel Clustering Algorithms Vector Quantization Segmentation for Head Pose Estimation Neural Network Detectors for Composite Hypothesis Tests Automatic Sound Classification for Improving Speech Intelligibility in Hearing Aids Using a Layered Structure Directed Laplacian Kernels for Link Analysis Pruning Adaptive Boosting Ensembles by Means of a Genetic Algorithm On the Fusion of Polynomial Kernels for Support Vector Classifiers Speech and Gesture Recognition-Based Robust Language Processing Interface in Noise Environment Heterogeneous Answer Acquisition Methods in Encyclopedia QA Face Recognition Using DCT and Hierarchical RBF Model Chaotic Dynamics for Avoiding Congestion in the Computer Network Combined Effects of Class Imbalance and Class Overlap on Instance-Based Classification Melt Index Predict by Radial Basis Function Network Based on Principal Component Analysis Thinking Capability of Saplings Growing Up Algorithm Functional Networks and the Lagrange Polynomial Interpolation The Evolution of OSI Network Management by Integrated the Expert Knowledge Learning the Complete-Basis-Functions Parameterization for the Optimization of Dynamic Molecular Alignment by ES Multi Criteria Wrapper Improvements to Naive Bayes Learning BP Neural Networks Combined with PLS Applied to Pattern Recognition of Vis/NIRs Speeding Up Shape Classification by Means of a Cyclic Dynamic Time Warping Lower Bound Using Genetic Algorithm for Network Status Learning and Worm Virus Detection Scheme Clustering by Integrating Multi-objective Optimization with Weighted K-Means and Validity Analysis Improving the Classification Accuracy of RBF and MLP Neural Networks Trained with Imbalanced Samples Learning Discrete Probability Distributions with a Multi-resolution Binary Tree Combining Unsupervised and Supervised Approaches to Feature Selection for Multivariate Signal Compression Cohesion Factors: Improving the Clustering Capabilities of Consensus Using Neural Networks to Detect Microfossil Teeth in Somosaguas Sur Paleontological Site A Fast Grid Search Method in Support Vector Regression Forecasting Time Series Fast Global {\itshape k}-Means with Similarity Functions Algorithm NN-Based Detector for Known Targets in Coherent Weibull Clutter ICA with Sparse Connections Two-Stage User Mobility Modeling for Intention Prediction for Location-Based Services Partition-Based Similarity Joins Using Diagonal Dimensions in High Dimensional Data Spaces Evolving Feed-forward Neural Networks Through Evolutionary Mutation Parameters Computer Interface Using Eye Tracking for Handicapped People Local Negative Correlation with Resampling Convex Perceptrons Hybridizing Cultural Algorithms and Local Search ICA and Genetic Algorithms for Blind Signal and Image Deconvolution and Deblurring Data Mining, Retrieval and Management Electroencephalogram Signals from Imagined Activities: A Novel Biometric Identifier for a Small Population Resolving Ambiguities in the Semantic Interpretation of Natural Language Questions Mining the K-Most Interesting Frequent Patterns Sequentially Discovering Non-taxonomic Relations from the Web A New Algorithm of Similarity Measuring for Multi-experts' Qualitative Knowledge Based on Outranking Relations in Case-Based Reasoning Methodology Comparing and Combining Spatial Dimension Reduction Methods in Face Verification A New Semi-supervised Dimension Reduction Technique for Textual Data Analysis CBR Model for the Intelligent Management of Customer Support Centers Non Parametric Local Density-Based Clustering for Multimodal Overlapping Distributions Application of Bidirectional Probabilistic Character Language Model in Handwritten Words Recognition Efficient Classification Method for Complex Biological Literature Using Text and Data Mining Combination Classifying Polyphony Music Based on Markov Model Two Phase Semi-supervised Clustering Using Background Knowledge Using Rough Set to Find the Factors That Negate the Typical Dependency of a Decision Attribute on Some Condition Attributes Automatic Extraction and Classification of Footwear Patterns Description of Combined Spatial Relations Between Broad Boundary Regions Based on Rough Set Active Sketch for Finding Primary Structures in Images Shape Matching Using Chord-Length Function Spectral High Resolution Feature Selection for Retrieval of Combustion Temperature Profiles Sentence Ordering in Extractive MDS Query Expansion with an Automatically Generated Thesaurus An Interactive Hybrid System for Identifying and Filtering Unsolicited E-mail Topological Tree Clustering of Web Search Results Reduced Attribute Oriented Inconsistency Handling in Decision Generation A Non-parametric Method for Data Clustering with Optimal Variable Weighting A Closed Model for Measuring Intangible Assets: A New Dimension of Profitability Applying Neural Networks Audio and Video Feature Fusion for Activity Recognition in Unconstrained Videos Multi-stage Classification for Audio Based Activity Recognition A Simple Approximation for Dynamic Time Warping Search in Large Time Series Database Regression Analisys of Segmented Parametric Software Cost Estimation Models Using Recursive Clustering Tool An Efficient Attribute Reduction Algorithm Conceptual Classification to Improve a Web Site Content Automated Learning of RVM for Large Scale Text Sets: Divide to Conquer Using Rules Discovery for the Continuous Improvement of e-Learning Courses Generating Adaptive Presentations of Hydrologic Behavior A New Measure for Query Disambiguation Using Term Co-occurrences Unsupervised Word Categorization Using Self-Organizing Maps and Automatically Extracted Morphs Effective Classification by Integrating Support Vector Machine and Association Rule Mining A Design of Dynamic Network Management System QoS Multicast Routing Based on Particle Swarm Optimization Evolutionary Search of Optimal Features Biased Minimax Probability Machine Active Learning for Relevance Feedback in Content-Based Image Retrieval Evidential Integration of Semantically Heterogeneous Aggregates in Distributed Databases with Imprecision Describing Customer Loyalty to Spanish Petrol Stations Through Rule Extraction Strangeness Minimisation Feature Selection with Confidence Machines Indexing and Mining of Graph Database Based on Interconnected Subgraph Evaluation of Decision Tree Pruning with Subadditive Penalties Categorization of Large Text Collections: Feature Selection for Training Neural Networks Towards Healthy Association Rule Mining (HARM): A Fuzzy Quantitative Approach State Aggregation in Higher Order Markov Chains for Finding Online Communities Functional Networks and Analysis of Variance for Feature Selection Automatic Categorization of Patent Applications Using Classifier Combinations Best Subset Feature Selection for Massive Mixed-Type Problems Planning Under Uncertainty with Abstraction Hierarchies Fusion of Domain Knowledge for Dynamic Learning in Transcriptional Networks An Improved Discrete Immune Network for Multimodal Optimization Bioinformatics and Bio-inspired Models Using Fuzzy Patterns for Gene Selection and Data Reduction on Microarray Data Applying GCS Networks to Fuzzy Discretized Microarray Data for Tumour Diagnosis Refractory Effects of Chaotic Neurodynamics for Finding Motifs from DNA Sequences Neighborhood-Based Clustering of Gene-Gene Interactions Gene Expression Profiling Using Flexible Neural Trees Multivariate Crosstalk Models Decision Making Association Rules for Recognition of Differential Gene Expression Profiles Application of Chemoinformatics to the Structural Elucidation of Natural Compounds Agents and Hybrid Systems Intelligent Coordinated Control of Multiple Teleoperated Robots SMas: A Shopping Mall Multiagent Systems Protecting Agent from Attack in Grid Computing II A Graph Transformation System Model of Dynamic Reorganization in Multi-agent Systems Efficient Search of Winning Strategies in Multi-agent Systems on Random Network: Importance of Local Solidarity Heterogeneous Domain Ontology for Location Based Information System in a Multi-agent Framework Intelligent Data Analysis for the Verification of Multi-Agent Systems Interactions Multi-agent Based Hybrid System for Dynamic Web-Content Adaptation Strategic Software Agents in Continuous Double Auction Under Dynamic Environments Student Modeling for Adaptive Teachable Agent to Enhance Interest and Comprehension An Agent-Based Model of Personal Web Communities A Conceptual Framework for Automated Negotiation Systems Development of New IFC-BRIDGE Data Model and a Concrete Bridge Design System Using Multi-agents Multi-Agent Systems over RT-Java for a Mobile Robot Control Financial Engineering Financial Risk Modeling with Markov Chains CNY Realignment and USD Expectation: Empirical Study Based on RND Function of Currency Option Investment Selection and Risk Management for Insurance Corporation Knowledge-Based Risk Assessment Under Uncertainty in Engineering Projects Fuzzy Regression with Quadratic Programming: An Application to Financial Data Special Session on Nature-Inspired Date Technologies Improving Search in Unstructured P2P Systems: Intelligent Walks (I-Walks) Evolutionary Product-Unit Neural Networks for Classification Uncentered (Absolute) Correlation Clustering Method Fit for Establishing Theoretical SAPK/JNK Signaling Pathway in Human Soft Tissue Sarcoma Samples Guiding Genetic Program Based Data Mining Using Fuzzy Rules Neural Network Models for Language Acquisition: A Brief Survey Incorporating Knowledge in Evolutionary Prototype Selection Evidence Relationship Matrix and Its Application to D-S Evidence Theory for Information Fusion Soft Computing in Context-Sensitive Multidimensional Ranking Ontology-Based Classifier for Audio Scenes in Telemedicine PSO and ACO in Optimization Problems Constraints in Particle Swarm Optimization of Hidden Markov Models Nature-Inspired Approaches to Mining Trend Patterns in Spatial Databases A Proposal of Evolutionary Prototype Selection for Class Imbalance Problems MOVICAB-IDS: Visual Analysis of Network Traffic Data Streams for Intrusion Detection Maximum Likelihood Topology Preserving Ensembles Backmatter Since its establishment in Hong Kong in 1998,the international Intelligent Data Engineering and Automated Learning (IDEAL) conference has become a r- erence for researchers in both theoretical and practical aspects of learning and information processing, data mining, retrieval and management, bioinformatics and bio-inspired models, agents and hybrid systems and?nancial engineering. The purpose of IDEAL conferences has been to provide a broad and interd- ciplinary forum for scientists, researchers, and practitioners in these areas from around the world. A special feature of IDEAL conferences is cross-disciplinary exchange of ideas in emerging topics and application in these areas. Data ana- sis and engineering and associated learning paradigms are playing increasingly important roles in an increasing number of applications and?elds. The mul- disciplinary nature of contemporary research is pushing the boundaries and one of the principal aims of the IDEAL conferences is to promote interactions and collaborations across disciplines. This volume of Lecture Notes in Computer Science contains accepted - pers presented at IDEAL 2006 held at the University of Burgos, Spain, during, September 20-23, 2006. The conference received 557 submissions from over 40 countriesaroundtheworld, whichweresubsequentlyrefereedbytheProgramme Committeeandmanyadditionalreviewers. Afterrigorousreview,170top-quality papers were accepted and included in the proceedings. The acceptance rate was only 30%, which ensured an extremely high-quality standard of the conference. The buoyant number of submitted papers is a clear proof of the vitality and increased importance of the?elds related to IDEAL, and is also an indication of the rising popularity of the IDEAL conferences

this Book Constitutes The Refereed Proceedings Of The 7th International Conference On Intelligent Data Engineering And Automated Learning, Ideal 2006, Held In Burgos, Spain In September 2006.

the 170 Revised Full Papers Presented Were Carefully Reviewed And Selected From 557 Submissions. The Papers Are Organized In Topical Sections On Learning And Information Processing, Data Mining, Retrieval And Management, Bioinformatics And Bio-inspired Models, Agents And Hybrid Systems, Financial Engineering, As Well As A Special Session On Nature-inspired Date Technologies.