Table of Contents

• In Pursuit of Patterns in Data Reasoning from Data – The Rough Set WayZdzislaw Pawlak. 1-9 [doi]
• Toward a Theory of Hierarchical Definability (THD)Lotfi A. Zadeh. 10-12 [doi]
• Modelling Biological Phenomena with Rough SetsHenryk Jan Komorowski. 13 [doi]
• Database Mining on Derived AttributesTsau Young Lin. 14-32 [doi]
• A Proposed Evolutionary, Self-Organizing Automaton for the Control of Dynamic SystemsDavid W. Russell. 33-43 [doi]
• Rough Set Analysis of Preference-Ordered DataRoman Slowinski, Salvatore Greco, Benedetto Matarazzo. 44-59 [doi]
• Fuzzy Sets, Multi-valued Mappings, and Rough SetsI. Burhan Türksen. 60 [doi]
• Investigating the Choice of l and u Values in the Extended Variable Precision Rough Sets ModelMalcolm J. Beynon. 61-68 [doi]
• A Quantitative Analysis of Preclusivity vs. Similarity Based Rough ApproximationsGianpiero Cattaneo, Davide Ciucci. 69-76 [doi]
• Heyting Wajsberg Algebras as an Abstract Environment Linking Fuzzy and Rough SetsGianpiero Cattaneo, Davide Ciucci. 77-84 [doi]
• Dominance-Based Rough Set Approach Using Possibility and Necessity MeasuresSalvatore Greco, Masahiro Inuiguchi, Roman Slowinski. 85-92 [doi]
• Generalized Decision Algorithms, Rough Inference Rules, and Flow GraphsSalvatore Greco, Zdzislaw Pawlak, Roman Slowinski. 93-104 [doi]
• Generalized Rough Sets and Rule ExtractionMasahiro Inuiguchi, Tetsuzo Tanino. 105-112 [doi]
• Towards a Mereological System for Direct Products and RelationsRyszard Janicki. 113-122 [doi]
• On the Structure of Rough ApproximationsJouni Järvinen. 123-130 [doi]
• Modification of Weights of Conflict Profile s Elements and Dependencies of Attributes in Consensus ModelRadoslaw Katarzyniak, Ngoc Thanh Nguyen. 131-138 [doi]
• Reasoning about Information Granules Based on Rough LogicQing Liu, S. L. Jiang. 139-143 [doi]
• A Rough Set Framework for Learning in a Directed Acyclic GraphHerman Midelfart, Henryk Jan Komorowski. 144-155 [doi]
• On Compressible Information SystemsMikhail Moshkov. 156-160 [doi]
• Functional Dependencies in Relational Expressions Based on Or-SetsMichinori Nakata, Tetsuya Murai. 161-166 [doi]
• On Asymptotic Properties of Rough-Set-Theoretic Approximations. Fractal Dimension, Exact Sets, and Rough Inclusion in Potentially Infinite Information SystemsLech Polkowski. 167-174 [doi]
• About Tolerance and Similarity Relations in Information SystemsJacek Pomykala. 175-182 [doi]
• Rough Sets, Guarded Command Language, and Decision RulesFrederick V. Ramsey, James J. Alpigini. 183-188 [doi]
• Collaborative Query Processing in DKS Controlled by ReductsZbigniew W. Ras, Agnieszka Dardzinska. 189-196 [doi]
• A New Method for Determining of Extensions and Restrictions of Information SystemsWojciech Rzasa, Zbigniew Suraj. 197-204 [doi]
• A Logic Programming Framework for Rough SetsAida Vitória, Jan Maluszynski. 205-212 [doi]
• Attribute Core of Decision TableG. Y. Wang. 213-217 [doi]
• Signal Analysis Using Rough IntegralsMaciej Borkowski. 218-225 [doi]
• How Much Privacy? - A System to Safe Guard Personal Privacy while Releasing DatabasesYi-Ting Chiang, Yu-Cheng Chiang, Tsan-sheng Hsu, Churn-Jung Liau, Da-Wei Wang. 226-233 [doi]
• Rough Clustering: An Alternative to Find Meaningful Clusters by Using the Reducts from a DatasetHércules Antonio do Prado, Paulo Martins Engel, Homero Chaib Filho. 234-238 [doi]
• Concept Learning with Approximation: Rough Version SpacesVincent Dubois, Mohamed Quafafou. 239-246 [doi]
• Variable Consistency Monotonic Decision TreesSilvio Giove, Salvatore Greco, Benedetto Matarazzo, Roman Slowinski. 247-254 [doi]
• Importance and Interaction of Conditions in Decision RulesSalvatore Greco, Benedetto Matarazzo, Roman Slowinski, Jerzy Stefanowski. 255-262 [doi]
• Time Complexity of Rough Clustering: GAs versus K-MeansPawan Lingras, Y. Y. Yao. 263-270 [doi]
• Induction of Decision Rules and Classification in the Valued Tolerance ApproachJerzy Stefanowski, Alexis Tsoukiàs. 271-278 [doi]
• Time Series Model Mining with Similarity-Based Neuro-Fuzzy Networks and Genetic Algorithms: A Parallel ImplementationJulio J. Valdés, Gabriel Mateescu. 279-288 [doi]
• Closeness of Performance Map Information Granules: A Rough Set ApproachJames J. Alpigini. 289-295 [doi]
• Granular Computing on Binary RelationsTsau Young Lin. 296-299 [doi]
• Measures of Inclusion and Closeness of Information Granules: A Rough Set ApproachJames F. Peters, Andrzej Skowron, Zbigniew Suraj, Maciej Borkowski, Wojciech Rzasa. 300-307 [doi]
• Rough Neurocomputing: A Survey of Basic Models of NeurocomputationJames F. Peters, Marcin S. Szczuka. 308-315 [doi]
• Rough Neurocomputing Based on Hierarchical ClassifiersAndrzej Skowron, Jaroslaw Stepaniuk, James F. Peters. 316-323 [doi]
• Using Granular Objects in Multi-source Data FusionRonald R. Yager. 324-330 [doi]
• Induction of Classification Rules by Granular ComputingJ. T. Yao, Y. Y. Yao. 331-338 [doi]
• Acquisition Methods for Contextual Weak IndependenceCory J. Butz, Manon J. Sanscartier. 339-343 [doi]
• A Method for Detecting Context-Specific Independence in Conditional Probability TablesCory J. Butz, Manon J. Sanscartier. 344-348 [doi]
• Properties of Weak Conditional IndependenceCory J. Butz, Manon J. Sanscartier. 349-356 [doi]
• A Proposal of Probability of Rough Event Based on Probability of Fuzzy EventRolly Intan, Masao Mukaidono. 357-364 [doi]
• Approximate Bayesian Network ClassifiersDominik Slezak, Jakub Wroblewski. 365-372 [doi]
• Accuracy and Coverage in Rough Set Rule InductionShusaku Tsumoto. 373-380 [doi]
• Statistical Test for Rough Set Approximation Based on Fisher s Exact TestShusaku Tsumoto. 381-388 [doi]
• Triangulation of Bayesian Networks: A Relational Database PerspectiveS. K. Michael Wong, Dan Wu, Cory J. Butz. 389-396 [doi]
• A New Version of Rough Set Exploration SystemJan G. Bazan, Marcin S. Szczuka, Jakub Wroblewski. 397-404 [doi]
• Local Attribute Value Grouping for Lazy Rule InductionGrzegorz Góra, Arkadiusz Wojna. 405-412 [doi]
• Incomplete Data Decomposition for ClassificationRafal Latkowski. 413-420 [doi]
• Extension of Relational Management Systems with Data Mining CapabilitiesJuan Francisco Martínez Sarrías, Anita Wasilewska, Michael Hadjimichael, Covadonga Fernández, Ernestina Menasalvas Ruiz. 421-424 [doi]
• Reducing Number of Decision Rules by JoiningMichal Mikolajczyk. 425-432 [doi]
• Scalable Classification Method Based on Rough SetsHung Son Nguyen. 433-440 [doi]
• Parallel Data Mining Experimentation Using Flexible ConfigurationsJosé M. Peña Sánchez, F. Javier Crespo, Ernestina Menasalvas Ruiz, Víctor Robles. 441-448 [doi]
• An Optimization of Apriori Algorithm through the Usage of Parallel I/O and HintsMaría S. Pérez, Ramón A. Pons, Félix García, Jesús Carretero, María L. Córdoba. 449-452 [doi]
• Patterns in Information MapsAndrzej Skowron, Piotr Synak. 453-460 [doi]
• Discernibility Matrix Approach to Exception AnalysisMin Zhao, Jue Wang. 461-466 [doi]
• Gastric Cancer Data Mining with Ordered InformationNing Zhong, Juzhen Dong, Yiyu Yao, Setsuo Ohsuga. 467-478 [doi]
• A Granular Approach for Analyzing the Degree of Affability of a Web SiteEsther Hochsztain, Socorro Millán, Ernestina Menasalvas Ruiz. 479-486 [doi]
• Comparison of Classification Methods for Customer Attrition AnalysisXiaohua Hu. 487-492 [doi]
• User Profile Model: A View from Artificial IntelligenceYuefeng Li, Y. Y. Yao. 493-496 [doi]
• Mining the Client s Life Cycle Behaviour in the WebOscar Marbán, Javier Segovia, Juan J. Cuadrado, César Montes. 497-505 [doi]
• PagePrompter: An Intelligent Web Agent Created Using Data Mining TechniquesY. Y. Yao, Howard J. Hamilton, Xuewei Wang. 506-513 [doi]
• VPRSM Approach to WEB SearchingWojciech Ziarko, Xue-fei. 514-521 [doi]
• Rough Set Approach to the Survival AnalysisJan G. Bazan, Antoni Osmólski, Andrzej Skowron, Dominik Slezak, Marcin S. Szczuka, Jakub Wroblewski. 522-529 [doi]
• The Identification of Low-Paying Workplaces: An Analysis Using the Variable Precision Rough Sets ModelMalcolm J. Beynon. 530-537 [doi]
• A Search for the Best Data Mining Method to Predict MelanomaJerzy W. Grzymala-Busse, Zdzislaw S. Hippe. 538-545 [doi]
• Towards the Classification of Musical Works: A Rough Set ApproachMonika P. Hippe. 546-553 [doi]
• Segmentation of Medical Images Based on Approximations in Rough Set TheoryShoji Hirano, Shusaku Tsumoto. 554-563 [doi]
• Adaptive Robust Estimation for Filtering Motion VectorsSeok-Woo Jang, Essam A. El-Kwae, Hyung-Il Choi. 564-567 [doi]
• Rough Set Feature Selection and Diagnostic Rule Generation for Industrial ApplicationsSeungkoo Lee, Nicholas Propes, Guangfan Zhang, Yongsheng Zhao, George J. Vachtsevanos. 568-571 [doi]
• lambda-Connected Approximations for Rough SetsLi Chen. 572-577 [doi]
• Adaptive Classifier Construction: An Approach to Handwritten Digit RecognitionTuan Trung Nguyen. 578-585 [doi]
• The Application of Support Diagnose in Mitochondrial EncephalomyopathiesPiotr Paszek, Alicja Wakulicz-Deja. 586-593 [doi]
• Obstacle Classification by a Line-Crawling Robot: A Rough Neurocomputing ApproachJames F. Peters, Tae-Chon Ahn, Maciej Borkowski. 594-601 [doi]
• Rough Neural Network for Software Change PredictionSheela Ramanna. 602-609 [doi]
• Handling Spatial Uncertainty in Binary Images: A Rough Set Based ApproachD. Sinha, Phillip A. Laplante. 610-620 [doi]
• Evolutionary Algorithms and Rough Sets-Based Hybrid Approach to Classificatory Decomposition of Cortical Evoked PotentialsTomasz G. Smolinski, Grzegorz M. Boratyn, Mariofanna G. Milanova, Jacek M. Zurada, Andrzej Wrobel. 621-628 [doi]
• Rough Mereological Localization and NavigationAdam Szmigielski. 629-638 [doi]