The methods of the theory of rough sets have applications in many sub-areas of artificial intelligence including knowledge discovery, machine learning, formal reasoning in the presence of uncertainty, knowledge acquisition, and others.

An Overview of Knowledge Discovery in Databases: Recent Progress and Challenges.- Rough Sets and Knowledge Discovery: An Overview.- Search for Concepts and Dependencies in Databases.- Rough Sets and Concept Lattices.- Human-Computer Interfaces: DBLEARN and SystemX.- A Heuristic for Evaluating Databases for Knowledge Discovery with DBLEARN.- Knowledge Recognition, Rough Sets, and Formal Concept Lattices.- Quantifying Uncertainty of Knowledge Discovered from Databases.- Temporal Rules Discovery Using Datalogic/R+ with Stock Market Data.- A System Architecture for Database Mining Applications.- An Attribute-Oriented Rough Set Approach for Knowledge Discovery in Databases.- A Rough Set Model for Relational Databases.- Data Filtration: A Rough Set Approach.- Automated Discovery of Empirical Laws in a Science Laboratory.- Hard and Soft Sets.- Rough Set Analysis of Multi-Attribute Decision Problems.- Rough Set Semantics for Non-Classical Logics.- A Note on Categories of Information Systems.- On Rough Sets in Topological Boolean Algebras.- Approximation of Relations.- Variable Precision Rough Sets with Asymmetric Bounds.- Uncertain Reasoning with Interval-Set Algebra.- On a Logic of Information for Reasoning About Knowledge.- Rough Consequence and Rough Algebra.- Formal Description of Rough Sets.- Rough Sets: A Special Case of Interval Structures.- A Pure Logic-Algebraic Analysis of Rough Top and Rough Bottom Equalities.- A Novel Approach to the Minimal Cover Problem.- Algebraic Structures of Rough Sets.- Rough Concept Analysis.- Rough Approximate Operators: Axiomatic Rough Set Theory.- Finding Reducts in Composed Information Systems.- PRIMEROSE: Probabilistic Rule Induction Method Based on Rough Set Theory.- Comparison of Machine Learning and Knowledge Acquisition Methods of Rule Induction Based on Rough Sets.- AQ, Rough Sets, and Matroid Theory.- Rough Classifiers.- A General Two-Stage Approach to Inducing Rules from Examples.- An Incremental Learning Algorithm for Constructing Decision Rules.- Decision Trees for Decision Tables.- Fuzzy Reasoning and Rough Sets.- Fuzzy Representations in Rough Set Approximations.- Trusting an Information Agent.- Handling Various Types of Uncertainty in the Rough Set Approach.- Intelligent Image Filtering Using Rough Sets.- Multilayer Knowledge Base System for Speaker-Independent Recognition of Isolated Words.- Image Segmentation Based on the Indiscernibility Relation.- Accurate Edge Detection Using Rough Sets.- Rough Classification of Pneumonia Patients Using a Clinical Database.- Rough Sets Approach to Analysis of Data of Diagnostic Peritoneal Lavage Applied for Multiple Injuries Patients.- Neural Networks and Rough Sets — Comparison and Combination for Classification of Histological Pictures.- Towards a Parallel Rough Sets Computer.- Learning Conceptual Design Rules: A Rough Sets Approach.- Intelligent Control System Implementation to the Pipe Organ Instrument.- An Implementation of Decomposition Algorithm and its Application in Information Systems Analysis and Logic Synthesis.- ESEP: An Expert System for Environmental Protection.- Author Index.