International Journal of Man-Machine Studies
Instance-Based Learning Algorithms
Machine Learning
Analogy-making as perception: a computer model
Analogy-making as perception: a computer model
Inferential Theory of Learning as a Conceptual Basis for Multistrategy Learning
Machine Learning - Special issue on multistrategy learning
Variable precision rough set model
Journal of Computer and System Sciences
Tolerance approximation spaces
Fundamenta Informaticae - Special issue: rough sets
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Relational Data Mining
Discovery of Decision Rules by Matching New Objects Against Data Tables
RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
Rough Logic for Multi-Agent Systems
International Conference Logic at Work on Knowledge Representation and Reasoning Under Uncertainty, Logic at Work
Data Mining and Knowledge Discovery Handbook
Data Mining and Knowledge Discovery Handbook
Quality Measures in Data Mining (Studies in Computational Intelligence)
Quality Measures in Data Mining (Studies in Computational Intelligence)
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning)
Dominance-Based Rough Set Approach to Reasoning About Ordinal Data
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Category-Based Rough Induction
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Classification of Complex Structured Objects on the Base of Similarity Degrees
RSEISP '07 Proceedings of the international conference on Rough Sets and Intelligent Systems Paradigms
Approximation spaces in multi relational knowledge discovery
Transactions on rough sets VI
Improving rough classifiers using concept ontology
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Approximation spaces and information granulation
Transactions on Rough Sets III
Transactions on Rough Sets IV
Analogy-based reasoning in classifier construction
Transactions on Rough Sets IV
Rough sets and vague concept approximation: from sample approximation to adaptive learning
Transactions on Rough Sets V
Dominance-Based rough set approach to case-based reasoning
MDAI'06 Proceedings of the Third international conference on Modeling Decisions for Artificial Intelligence
Nearest neighbor pattern classification
IEEE Transactions on Information Theory
Approximation Spaces Based on Relations of Similarity and Dissimilarity of Objects
Fundamenta Informaticae - Special Issue on Concurrency Specification and Programming (CS&P)
Nearness of Objects: Extension of Approximation Space Model
Fundamenta Informaticae - Special Issue on Concurrency Specification and Programming (CS&P)
Calculi of Approximation Spaces
Fundamenta Informaticae - SPECIAL ISSUE ON CONCURRENCY SPECIFICATION AND PROGRAMMING (CS&P 2005) Ruciane-Nide, Poland, 28-30 September 2005
A Rough Set Approach to Multiple Classifier Systems
Fundamenta Informaticae - SPECIAL ISSUE ON CONCURRENCY SPECIFICATION AND PROGRAMMING (CS&P 2005) Ruciane-Nide, Poland, 28-30 September 2005
Satisfiability and Meaning of Formulas and Sets of Formulas in Approximation Spaces
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P 2004)
Spatio-Temporal Approximate Reasoning over Complex Objects
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P 2004)
A Graded Meaning of Formulas in Approximation Spaces
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P 2003)
Learning First-Order Rules: A Rough Set Approach
Fundamenta Informaticae - International Conference on Soft Computing and Distributed Processing (SCDP'2002)
RIONA: A New Classification System Combining Rule Induction and Instance-Based Learning
Fundamenta Informaticae
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In this article we discuss judgment of satisfiability of formulas of a knowledge representation language as an object classification task. Our viewpoint is that of the rough set theory (RST), and the descriptor language for Pawlak's information systems of a basic kind is taken as the study case. We show how certain analogy-based methods can be employed to judge satisfiability of formulas of that language.