Intelligent Data Engineering and Automated Learning - IDEAL 2004 : 5th International Conference, Exeter, UK, August 25-27, 2004. Proceedings

Zhen Rong Yang

ISBN 10: 3540228810 / ISBN 13: 9783540228813

Editore: Springer, Berlin, Springer, 2004

Riguardo questo articolo

Neuware - The Intelligent Data Engineering and Automated Learning (IDEAL) conf- ence series began in 1998 in Hong Kong, when the world started to experience information and data explosion and to demand for better, intelligent meth- ologies and techniques. It has since developed, enjoyed success in recent years, and become a unique annual international forum dedicated to emerging topics and technologies in intelligent data analysis and mining, knowledge discovery, automated learning and agent technology, as well as interdisciplinary appli- tions, especially bioinformatics. These techniques are common and applicable to many elds. The multidisciplinary nature of research nowadays is pushing the boundaries and one of the principal aims of the IDEAL conference is to p- mote interactions and collaborations between disciplines, which are bene cial and bringing fruitful solutions. This volume of Lecture Notes in Computer Science contains accepted papers presented at IDEAL 2004, held in Exeter, UK, August 25 27, 2004. The conf- ence received 272 submissions from all over the world, which were subsequently refereed by the ProgramCommittee. Among them 124 high-quality papers were accepted and included in the proceedings. IDEAL 2004 enjoyed outstanding keynote talks by distinguished guest speakers,Jim Austin, Mark Girolami, Ross King, Lei Xu and Robert Esnouf. This year IDEAL also teamed up with three international journals, namely the International Journal of Neural Systems,the Journal of Mathematical M- elling and Algorithms,and Neural Computing & Applications. Three special issues on Bioinformatics, Learning Algorithms,and Neural Networks & Data Mining, respectively, have been scheduled for selected papers from IDEAL 2004.

Codice articolo 9783540228813

Dati bibliografici

• Titolo: Intelligent Data Engineering and Automated Learning - IDEAL 2004 : 5th International Conference, Exeter, UK, August 25-27, 2004. Proceedings
• Editore: Springer, Berlin, Springer
• Data di pubblicazione: 2004
• Lingua: Inglese
• ISBN 10: 3540228810
• ISBN 13: 9783540228813
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 158 A x 35 P (millimetri) 235 millimetri di larghezza per 158 millimetri di altezza per 35 millimetri di profondità
• Peso: 1220 grammi

Descrizione articolo

Riassunto

The Intelligent Data Engineering and Automated Learning (IDEAL) conf- ence series began in 1998 in Hong Kong, when the world started to experience information and data explosion and to demand for better, intelligent meth- ologies and techniques. It has since developed, enjoyed success in recent years, and become a unique annual international forum dedicated to emerging topics and technologies in intelligent data analysis and mining, knowledge discovery, automated learning and agent technology, as well as interdisciplinary appli- tions, especially bioinformatics. These techniques are common and applicable to many ?elds. The multidisciplinary nature of research nowadays is pushing the boundaries and one of the principal aims of the IDEAL conference is to p- mote interactions and collaborations between disciplines, which are bene?cial and bringing fruitful solutions. This volume of Lecture Notes in Computer Science contains accepted papers presented at IDEAL 2004, held in Exeter, UK, August 25–27, 2004. The conf- ence received 272 submissions from all over the world, which were subsequently refereed by the ProgramCommittee. Among them 124 high-quality papers were accepted and included in the proceedings. IDEAL 2004 enjoyed outstanding keynote talks by distinguished guest speakers,Jim Austin, Mark Girolami, Ross King, Lei Xu and Robert Esnouf. This year IDEAL also teamed up with three international journals, namely the International Journal of Neural Systems,the Journal of Mathematical M- elling and Algorithms,and Neural Computing & Applications. Three special issues on Bioinformatics, Learning Algorithms,and Neural Networks & Data Mining, respectively, have been scheduled for selected papers from IDEAL 2004.

Contenuti

Bioinformatics.- Modelling and Clustering of Gene Expressions Using RBFs and a Shape Similarity Metric.- A Novel Hybrid GA/SVM System for Protein Sequences Classification.- Building Genetic Networks for Gene Expression Patterns.- SVM-Based Classification of Distant Proteins Using Hierarchical Motifs.- Knowledge Discovery in Lymphoma Cancer from Gene–Expression.- A Method of Filtering Protein Surface Motifs Based on Similarity Among Local Surfaces.- Qualified Predictions for Proteomics Pattern Diagnostics with Confidence Machines.- An Assessment of Feature Relevance in Predicting Protein Function from Sequence.- A New Artificial Immune System Algorithm for Clustering.- The Categorisation of Similar Non-rigid Biological Objects by Clustering Local Appearance Patches.- Unsupervised Dense Regions Discovery in DNA Microarray Data.- Visualisation of Distributions and Clusters Using ViSOMs on Gene Expression Data.- Prediction of Implicit Protein-Protein Interaction by Optimal Associative Feature Mining.- Exploring Dependencies Between Yeast Stress Genes and Their Regulators.- Poly-transformation.- Prediction of Natively Disordered Regions in Proteins Using a Bio-basis Function Neural Network.- The Effect of Image Compression on Classification and Storage Requirements in a High-Throughput Crystallization System.- PromSearch: A Hybrid Approach to Human Core-Promoter Prediction.- Data Mining and Knowledge Engineering.- Synergy of Logistic Regression and Support Vector Machine in Multiple-Class Classification.- Deterministic Propagation of Blood Pressure Waveform from Human Wrists to Fingertips.- Pre-pruning Decision Trees by Local Association Rules.- A New Approach for Selecting Attributes Based on Rough Set Theory.- A Framework for Mining Association Rules in Data Warehouses.- Intelligent Web Service Discovery in Large Distributed System.- The Application of K-Medoids and PAM to the Clustering of Rules.- A Comparison of Texture Teatures for the Classification of Rock Images.- A Mixture of Experts Image Enhancement Scheme for CCTV Images.- Integration of Projected Clusters and Principal Axis Trees for High-Dimensional Data Indexing and Query.- Unsupervised Segmentation on Image with JSEG Using Soft Class Map.- DESCRY: A Density Based Clustering Algorithm for Very Large Data Sets.- A Fuzzy Set Based Trust and Reputation Model in P2P Networks.- Video Based Human Behavior Identification Using Frequency Domain Analysis.- Mobile Data Mining by Location Dependencies.- An Algorithm for Artificial Intelligence-Based Model Adaptation to Dynamic Data Distribution.- On a Detection of Korean Prosody Phrases Boundaries.- A Collision Avoidance System for Autonomous Ship Using Fuzzy Relational Products and COLREGs.- Engineering Knowledge Discovery in Network Intrusion Detection.- False Alarm Classification Model for Network-Based Intrusion Detection System.- Exploiting Safety Constraints in Fuzzy Self-organising Maps for Safety Critical Applications.- Surface Spatial Index Structure of High-Dimensional Space.- Generating and Applying Rules for Interval Valued Fuzzy Observations.- Automatic Video Shot Boundary Detection Using Machine Learning.- On Building XML Data Warehouses.- A Novel Method for Mining Frequent Subtrees from XML Data.- Mining Association Rules Using Relative Confidence.- Multiple Classifiers Fusion System Based on the Radial Basis Probabilistic Neural Networks.- An Effective Distributed Privacy-Preserving Data Mining Algorithm.- Dimensionality Reduction with Image Data.- Implicit Fitness Sharing Speciation and Emergent Diversity in Tree Classifier Ensembles.- Improving Decision Tree Performance Through Induction- and Cluster-Based Stratified Sampling.- Learning to Classify Biomedical Terms Through Literature Mining and Genetic Algorithms.- PRICES: An Efficient Algorithm for Mining Association Rules.- Combination of SVM Knowledge for Microcalcification Detection in Digital Mammograms.- Char: An Automatic Way to Describe Characteristics of Data.- Two Methods for Automatic 3D Reconstruction from Long Un-calibrated Sequences.- Wrapper for Ranking Feature Selection.- Simultaneous Feature Selection and Weighting for Nearest Neighbor Using Tabu Search.- Fast Filtering of Structural Similarity Search Using Discovery of Topological Patterns.- Detecting Worm Propagation Using Traffic Concentration Analysis and Inductive Learning.- Comparing Study for Detecting Microcalcifications in Digital Mammogram Using Wavelets.- A Hybrid Multi-layered Speaker Independent Arabic Phoneme Identification System.- Feature Selection for Natural Disaster Texts Classification Using Testors.- Mining Large Engineering Data Sets on the Grid Using AURA.- Self-tuning Based Fuzzy PID Controllers: Application to Control of Nonlinear HVAC Systems.- Ontology-Based Web Navigation Assistant.- A Hybrid Fuzzy-Neuro Model for Preference-Based Decision Analysis.- Combining Rules for Text Categorization Using Dempster’s Rule of Combination.- Genetic Program Based Data Mining for Fuzzy Decision Trees.- Automating Co-evolutionary Data Mining.- Topological Tree for Web Organisation, Discovery and Exploration.- New Medical Diagnostic Method for Oriental Medicine Using BYY Harmony Learning.- An Intelligent Topic-Specific Crawler Using Degree of Relevance.- Development of a Global and Integral Model of Business Management Using an Unsupervised Model.- Spam Mail Detection Using Artificial Neural Network and Bayesian Filter.- An Integrated Approach to Automatic Indoor Outdoor Scene Classification in Digital Images.- Using Fuzzy Sets in Contextual Word Similarity.- Summarizing Time Series: Learning Patterns in ‘Volatile’ Series.- Cosine Transform Priors for Enhanced Decoding of Compressed Images.- Partial Discharge Classification Through Wavelet Packets of Their Modulated Ultrasonic Emission.- A Hybrid Optimization Method of Multi-objective Genetic Algorithm (MOGA) and K-Nearest Neighbor (KNN) Classifier for Hydrological Model Calibration.- Cluster-Based Visualisation of Marketing Data.- Dynamic Symbolization of Streaming Time Series.- A Clustering Model for Mining Evolving Web User Patterns in Data Stream Environment.- An Improved Constructive Neural Network Ensemble Approach to Medical Diagnoses.- Spam Classification Using Nearest Neighbour Techniques.- Learning Algorithms and Systems.- Kernel Density Construction Using Orthogonal Forward Regression.- Orthogonal Least Square with Boosting for Regression.- New Applications for Object Recognition and Affine Motion Estimation by Independent Component Analysis.- Personalized News Reading via Hybrid Learning.- Mercer Kernel, Fuzzy C-Means Algorithm, and Prototypes of Clusters.- DIVACE: Diverse and Accurate Ensemble Learning Algorithm.- Parallel Processing for Movement Detection in Neural Networks with Nonlinear Functions.- Combining Multiple k-Nearest Neighbor Classifiers Using Different Distance Functions.- Finding Minimal Addition Chains Using Ant Colony.- Combining Local and Global Models to Capture Fast and Slow Dynamics in Time Series Data.- A Variable Metric Probabilistic k-Nearest-Neighbours Classifier.- Feature Word Tracking in Time Series Documents.- Combining Gaussian Mixture Models.- Global Convergence of Steepest Descent for Quadratic Functions.- Boosting Orthogonal Least Squares Regression.- Local Separation Property of the Two-Source ICA Problem with the One-Bit-Matching Condition.- Two Further Gradient BYY Learning Rules for Gaussian Mixture with Automated Model Selection.- Improving Support Vector Solutions by Selecting a Sequence of Training Subsets.- Machine Learning for Matching Astronomy Catalogues.- Boosting the Tree Augmented Naïve Bayes Classifier.- Clustering Model Selection for Reduced Support Vector Machines.- Generating the Reduced Set by Systematic Sampling.- Experimental Comparison of Classification Uncertainty for Randomised and Bayesian Decision Tree Ensembles.- Policy Gradient Method for Team Markov Games.- An Information Theoretic Optimal Classifier for Semi-supervised Learning.- Improving Evolutionary Algorithms by a New Smoothing Technique.- In-Situ Learning in Multi-net Systems.- Multi-objective Genetic Algorithm Based Method for Mining Optimized Fuzzy Association Rules.- Co-training from an Incremental EM Perspective.- Locally Tuned General Regression for Learning Mixture Models Using Small Incomplete Data Sets with Outliers and Overlapping Classes.- Financial Engineering.- Credit Risks of Interest Rate Swaps: A Comparative Study of CIR and Monte Carlo Simulation Approach.- Cardinality Constrained Portfolio Optimisation.- Stock Trading by Modelling Price Trend with Dynamic Bayesian Networks.- Detecting Credit Card Fraud by Using Questionnaire-Responded Transaction Model Based on Support Vector Machines.- Volatility Forecasts in Financial Time Series with HMM-GARCH Models.- Agent Technologies.- User Adaptive Answers Generation for Conversational Agent Using Genetic Programming.- Comparing Measures of Agreement for Agent Attitudes.- Hierarchical Agglomerative Clustering for Agent-Based Dynamic Collaborative Filtering.- Learning Users’ Interests in a Market-Based Recommender System.- Visualisation of Multi-agent System Organisations Using a Self-organising Map of Pareto Solutions.