What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Statistics
His primary areas of investigation include Rough set, Dominance-based rough set approach, Data mining, Decision rule and Set.
In general Rough set, his work in Decision table is often linked to Context linking many areas of study.
His Dominance-based rough set approach study is related to the wider topic of Artificial intelligence.
Roman Słowiński interconnects Machine learning and Decision matrix in the investigation of issues within Artificial intelligence.
His Data mining study combines topics in areas such as Information system, Management information systems, Bayesian probability and Extension.
His Decision rule research incorporates themes from Weighted sum model, Decision problem, Rule of inference and Linear discriminant analysis.
His most cited work include:
- Rough sets (6144 citations)
- Rough sets theory for multicriteria decision analysis (1265 citations)
- Rough Sets and Current Trends in Computing (1081 citations)
What are the main themes of his work throughout his whole career to date?
Rough set, Dominance-based rough set approach, Artificial intelligence, Decision rule and Data mining are his primary areas of study.
His work carried out in the field of Rough set brings together such families of science as Fuzzy set, Set, Mathematical optimization, Algorithm and Monotonic function.
His work on Multicriteria classification as part of general Dominance-based rough set approach research is frequently linked to Context, thereby connecting diverse disciplines of science.
Roman Słowiński has researched Artificial intelligence in several fields, including Ranking, Machine learning, Decision problem and Pattern recognition.
His Decision rule study incorporates themes from Decision tree, Weighted sum model, Optimal decision, Multiple-criteria decision analysis and Decision analysis.
The concepts of his Data mining study are interwoven with issues in Bayesian probability, Management information systems and Extension.
He most often published in these fields:
- Rough set (56.01%)
- Dominance-based rough set approach (42.57%)
- Artificial intelligence (40.53%)
What were the highlights of his more recent work (between 2014-2021)?
- Rough set (56.01%)
- Mathematical optimization (32.18%)
- Dominance-based rough set approach (42.57%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Rough set, Mathematical optimization, Dominance-based rough set approach, Artificial intelligence and Preference.
Roman Słowiński undertakes multidisciplinary investigations into Rough set and Dominance in his work.
His Mathematical optimization research is multidisciplinary, relying on both Set, Decision problem and Pairwise comparison.
Dominance-based rough set approach is the subject of his research, which falls under Data mining.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning and Pattern recognition.
His Preference research is multidisciplinary, incorporating perspectives in Sorting, Ordinal regression and Bellman equation.
Between 2014 and 2021, his most popular works were:
- Forty years of the European Journal of Operational Research: A bibliometric overview (150 citations)
- Multiple Criteria Hierarchy Process for ELECTRE Tri methods (63 citations)
- Multiple Criteria Hierarchy Process for ELECTRE Tri methods (63 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
The scientist’s investigation covers issues in Mathematical optimization, Decision problem, Multiple-criteria decision analysis, Rough set and Artificial intelligence.
His studies deal with areas such as Set and Pairwise comparison as well as Mathematical optimization.
His Decision problem research integrates issues from Structure, Ordinal regression, Decision aiding and Hierarchy.
His biological study deals with issues like Management science, which deal with fields such as Decision support system, Structuring and Technical support.
His Rough set research includes themes of Unification, Decision rule and Class information.
As part of one scientific family, Roman Słowiński deals mainly with the area of Artificial intelligence, narrowing it down to issues related to the Machine learning, and often Data mining.
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