Tolerance approximation spaces
Fundamenta Informaticae - Special issue: rough sets
Knowledge discovery by application of rough set models
Rough set methods and applications
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Machine Learning
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems
Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems
Rough-Fuzzy Hybridization: A New Trend in Decision Making
Rough-Fuzzy Hybridization: A New Trend in Decision Making
Relational Data Mining
Data Transformation and Rough Sets
PKDD '98 Proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery
The generic rough set inductive logic programming (gRS--ILP) model
Data mining, rough sets and granular computing
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
Description and classification of complex structured objects by applying similarity measures
International Journal of Approximate Reasoning
Satisfiability of Formulas from the Standpoint of Object Classification: The RST Approach
Fundamenta Informaticae - Concurrency Specification and Programming (CS&P)
Approximation spaces in multi relational knowledge discovery
Transactions on rough sets VI
Similarity-Based Classification in Relational Databases
Fundamenta Informaticae
Satisfiability judgement under incomplete information
Transactions on Rough Sets XI
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The aim of this paper is to introduce and investigate an algorithm RSRL for finding first--order logic rules. Rough set methodology is used in the process of selecting literals which may be a part of a rule. The criterion of selecting a literal is as follows: only such a literal is selected, which added to the rule makes the rule discerning the most examples which were indiscernible so far.