| In Pursuit of Patterns in Data Reasoning from Data: The Rough Set Way | p. 1 |
| Toward a Theory of Hierarchical Definability (THD) (Causality Is Undefinable) | p. 10 |
| Modelling Biological Phenomena with Rough Sets | p. 13 |
| Database Mining on Derived Attributes (Granular and Rough Computing Approach) | p. 14 |
| A Proposed Evolutionary, Self-Organizing Automation for the Control of Dynamic Systems | p. 33 |
| Rough Set Analysis of Preference-Ordered Data | p. 44 |
| Fuzzy Sets, Multi-valued Mappings, and Rough Sets | p. 60 |
| Investigating the Choice of l and u Values in the Extended Variable Precision Rough Sets Model | p. 61 |
| A Quantitative Analysis of Preclusivity vs. Similarity Based Rough Approximations | p. 69 |
| Heyting Wajsberg Algebras as an Abstract Environment Linking Fuzzy and Rough Sets | p. 77 |
| Dominance-Based Rough Set Approach Using Possibility and Necessity Measures | p. 85 |
| Generalized Decision Algorithms, Rough Inference Rules, and Flow Graphs | p. 93 |
| Generalized Rough Sets and Rule Extraction | p. 105 |
| Towards a Mereological System for Direct Products and Relations | p. 113 |
| On the Structure of Rough Approximations | p. 123 |
| Modification of Weights of Conflict Profile's Elements and Dependencies of Attributes in Consensus Model | p. 131 |
| Reasoning about Information Granules Based on Rough Logic | p. 139 |
| A Rough Set Framework for Learning in a Directed Acyclic Graph | p. 144 |
| On Compressible Information Systems | p. 156 |
| Functional Dependencies in Relational Expressions Based on Or-Sets | p. 161 |
| On Asymptotic Properties of Rough-Set-Theoretic Approximations. Fractal Dimension, Exact Sets, and Rough Inclusion in Potentially Infinite Information Systems | p. 167 |
| About Tolerance and Similarity Relations in Information Systems | p. 175 |
| Rough Sets, Guarded Command Language, and Decision Rules | p. 183 |
| Collaborative Query Processing in DKS Controlled by Reducts | p. 189 |
| A New Method for Determining of Extensions and Restrictions of Information Systems | p. 197 |
| A Logic Programming Framework for Rough Sets | p. 205 |
| Attribute Core of Decision Table | p. 213 |
| Signal Analysis Using Rough Integrals | p. 218 |
| How Much Privacy? - A System to Safe Guard Personal Privacy while Releasing Databases | p. 226 |
| Rough Clustering: An Alternative to Find Meaningful Clusters by Using the Reducts from a Dataset | p. 234 |
| Concept Learning with Approximation: Rough Version Spaces | p. 239 |
| Variable Consistency Monotonic Decision Trees | p. 247 |
| Importance and Interaction of Conditions in Decision Rules | p. 255 |
| Time Complexity of Rough Clustering: GAs versus K-Means | p. 263 |
| Induction of Decision Rules and Classification in the Valued Tolerance Approach | p. 271 |
| Time Series Model Mining with Similarity-Based Neuro-fuzzy Networks and Genetic Algorithms: A Parallel Implementation | p. 279 |
| Closeness of Performance Map Information Granules: A Rough Set Approach | p. 289 |
| Granular Computing on Binary Relations (Analysis of Conflict and Chinese Wall Security Policy) | p. 296 |
| Measures of Inclusion and Closeness of Information Granules: A Rough Set Approach | p. 300 |
| Rough Neurocomputing: A Survey of Basic Models of Neurocomputation | p. 308 |
| Rough Neurocomputing Based on Hierarchical Classifiers | p. 316 |
| Using Granular Objects in Multi-source Data Fusion | p. 324 |
| Induction of Classification Rules by Granular Computing | p. 331 |
| Acquisition Methods for Contextual Weak Independence | p. 339 |
| A Method for Detecting Context-Specific Independence in Conditional Probability Tables | p. 344 |
| Properties of Weak Conditional Independence | p. 349 |
| A Proposal of Probability of Rough Event Based on Probability of Fuzzy Event | p. 357 |
| Approximate Bayesian Network Classifiers | p. 365 |
| Accuracy and Coverage in Rough Set Rule Induction | p. 373 |
| Statistical Test for Rough Set Approximation Based on Fisher's Exact Test | p. 381 |
| Triangulation of Bayesian Networks: A Relational Database Perspective | p. 389 |
| A New Version of Rough Set Exploration System | p. 397 |
| Local Attribute Value Grouping for Lazy Rule Induction | p. 405 |
| Incomplete Data Decomposition for Classification | p. 413 |
| Extension of Relational Management Systems with Data Mining Capabilities | p. 421 |
| Reducing Number of Decision Rules by Joining | p. 425 |
| Scalable Classification Method Based on Rough Sets | p. 433 |
| Parallel Data Mining Experimentation Using Flexible Configurations | p. 441 |
| An Optimization of Apriori Algorithm through the Usage of Parallel I/O and Hints | p. 449 |
| Patterns in Information Maps | p. 453 |
| Discernibility Matrix Approach to Exception Analysis | p. 461 |
| Gastric Cancer Data Mining with Ordered Information | p. 467 |
| A Granular Approach for Analyzing the Degree of Affability of a Web Site | p. 479 |
| Comparison of Classification Methods for Customer Attrition Analysis | p. 487 |
| User Profile Model: A View from Artificial Intelligence | p. 493 |
| Mining the Client's Life Cycle Behaviour in the Web | p. 497 |
| PagePrompter: An Intelligent Web Agent Created Using Data Mining Techniques | p. 506 |
| VPRSM Approach to WEB Searching | p. 514 |
| Rough Set Approach to the Survival Analysis | p. 522 |
| The Identification of Low-Paying Workplaces: An Analysis Using the Variable Precision Rough Sets Model | p. 530 |
| A Search for the Best Data Mining Method to Predict Melanoma | p. 538 |
| Towards the Classification of Musical Works: A Rough Set Approach | p. 546 |
| Segmentation of Medical Images Based on Approximations in Rough Set Theory | p. 554 |
| Adaptive Robust Estimation for Filtering Motion Vectors | p. 564 |
| Rough Set Feature Selection and Diagnostic Rule Generation for Industrial Applications | p. 568 |
| [lambda]-Connected Approximations for Rough Sets | p. 572 |
| Adaptive Classifier Construction: An Approach to Handwritten Digit Recognition | p. 578 |
| The Application of Support Diagnose in Mitochondrial Encephalomyopathies | p. 586 |
| Obstacle Classification by a Line-Crawling Robot: A Rough Neurocomputing Approach | p. 594 |
| Rough Neural Network for Software Change Prediction | p. 602 |
| Handling Spatial Uncertainty in Binary Images: A Rough Set Based Approach | p. 610 |
| Evolutionary Algorithms and Rough Sets-Based Hybrid Approach to Classificatory Decomposition of Cortical Evoked Potentials | p. 621 |
| Rough Mereological Localization and Navigation | p. 629 |
| Author Index | p. 639 |
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