Rough Sets Turn 40: From Information Systems to Intelligent Systems | 1 | 0.36 | 2022 |
Correction to: Interactive computations: toward risk management in interactive intelligent systems | 0 | 0.34 | 2019 |
Concept Approximation Based on Rough Sets and Judgment. | 0 | 0.34 | 2019 |
A Classifier Based on a Decision Tree with Temporal Cuts. | 1 | 0.36 | 2019 |
Linking Reaction Systems with Rough Sets. | 0 | 0.34 | 2019 |
Information flow in logic for distributed systems: Extending graded consequence. | 1 | 0.34 | 2019 |
Local rough set: A solution to rough data analysis in big data. | 17 | 0.49 | 2018 |
Rough Sets and Sorites Paradox. | 1 | 0.35 | 2018 |
Interactive Logical Structures. | 0 | 0.34 | 2017 |
A Classifier Based on a Decision Tree with Verifying Cuts. | 5 | 0.56 | 2016 |
Rough Sets and Interactive Granular Computing | 2 | 0.35 | 2016 |
Complex Adaptive Systems And Interactive Granular Computing | 0 | 0.34 | 2016 |
Data science, big data and granular mining | 7 | 0.45 | 2015 |
Generalized Quantifiers in the Context of Rough Set Semantics. | 0 | 0.34 | 2015 |
Interactive Rough-Granular Computing in Wisdom Technology | 0 | 0.34 | 2013 |
Interactive Computations: Toward Risk Management in Interactive Intelligent Systems. | 0 | 0.34 | 2013 |
Interactive Complex Granules | 2 | 0.35 | 2013 |
Rough Set Based Reasoning About Changes | 6 | 0.45 | 2012 |
Rough Derivatives as Dynamic Granules in Rough Granular Calculus. | 0 | 0.34 | 2012 |
Function Approximation and Quality Measures in Rough-Granular Systems | 5 | 0.44 | 2011 |
An Introduction to Perception Based Computing | 6 | 0.65 | 2010 |
Interactive Rough-Granular Computing in Pattern Recognition | 4 | 0.41 | 2009 |
Wisdom Technology: A Rough-Granular Approach | 20 | 0.85 | 2009 |
Rough-Granular Computing in Human-Centric Information Processing. | 5 | 0.42 | 2009 |
Maximal consistent extensions of information systems relative to their theories | 11 | 0.83 | 2008 |
Extracting Relevant Information about Reduct Sets from Data Tables | 5 | 0.42 | 2008 |
Comparison of lazy classification algorithms based on deterministic and inhibitory decision rules | 6 | 0.60 | 2008 |
Two Families of Classification Algorithms | 9 | 0.79 | 2007 |
Approaches to Conflict Dynamics Based on Rough Sets | 7 | 0.52 | 2007 |
Rough Sets and Intelligent Systems Paradigms, International Conference, RSEISP 2007, Warsaw, Poland, June 28-30, 2007, Proceedings | 76 | 7.21 | 2007 |
Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, Warsaw, Poland, September 17-21, 2007, Proceedings | 63 | 7.08 | 2007 |
On Minimal Rule Sets for Almost All Binary Information Systems | 7 | 0.61 | 2007 |
Rough Set Approach to Behavioral Pattern Identification | 4 | 0.41 | 2007 |
Rough sets: Some extensions | 411 | 14.37 | 2007 |
Approximation space-based socio-technical conflict model | 1 | 0.36 | 2007 |
Nearness of Objects: Extension of Approximation Space Model | 39 | 2.06 | 2007 |
Generalized conflict and resolution model with approximation spaces | 9 | 0.59 | 2006 |
Approximate Reasoning in MAS: Rough Set Approach | 3 | 0.42 | 2006 |
Transactions on rough sets VIII | 100 | 21.59 | 2006 |
Multimodal Classification: Case Studies | 19 | 0.83 | 2006 |
Calculi of Approximation Spaces | 46 | 1.63 | 2006 |
Planning based on reasoning about information changes | 4 | 0.46 | 2006 |
Rough sets and vague concept approximation: from sample approximation to adaptive learning | 30 | 1.02 | 2006 |
Automatic planning of treatment of infants with respiratory failure through rough set modeling | 16 | 0.64 | 2006 |
Some contributions by zdzisław pawlak | 1 | 0.34 | 2006 |
On testing membership to maximal consistent extensions of information systems | 10 | 0.91 | 2006 |
Modelling Complex Patterns by Information Systems | 9 | 0.63 | 2005 |
On-Line elimination of non-relevant parts of complex objects in behavioral pattern identification | 17 | 1.29 | 2005 |
Spatio-Temporal Approximate Reasoning over Complex Objects | 11 | 0.55 | 2005 |
Rough sets and higher order vagueness | 8 | 0.94 | 2005 |