H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 58 Citations 22,282 272 World Ranking 1744 National Ranking 3

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Programming language

Andrzej Skowron focuses on Rough set, Artificial intelligence, Data mining, Dominance-based rough set approach and Knowledge extraction. The concepts of his Rough set study are interwoven with issues in Mereology, Theoretical computer science and Decision rule. His studies in Theoretical computer science integrate themes in fields like Algorithm, Boolean function, Parameterized complexity, Fuzzy logic and Information system.

His Decision rule study combines topics from a wide range of disciplines, such as Decision tree, Machine learning, Set, Decision table and Boolean reasoning. He combines subjects such as Soft computing and Feature selection with his study of Data mining. His Dominance-based rough set approach research incorporates elements of Variable and Kansei engineering.

His most cited work include:

  • Rudiments of rough sets (1728 citations)
  • The Discernibility Matrices and Functions in Information Systems (1424 citations)
  • Rough sets: Some extensions (1022 citations)

What are the main themes of his work throughout his whole career to date?

Andrzej Skowron spends much of his time researching Rough set, Artificial intelligence, Granular computing, Theoretical computer science and Data mining. His Rough set research is multidisciplinary, incorporating elements of Algorithm, Knowledge extraction and Information system. His Artificial intelligence research is multidisciplinary, relying on both Machine learning, Mereology and Pattern recognition.

His work carried out in the field of Granular computing brings together such families of science as Judgement, Complex system, Soft computing and Domain knowledge. His Theoretical computer science research includes elements of Computation, Approximate reasoning and Knowledge representation and reasoning. His research combines Fuzzy set and Data mining.

He most often published in these fields:

  • Rough set (65.28%)
  • Artificial intelligence (37.50%)
  • Granular computing (24.77%)

What were the highlights of his more recent work (between 2012-2020)?

  • Rough set (65.28%)
  • Granular computing (24.77%)
  • Artificial intelligence (37.50%)

In recent papers he was focusing on the following fields of study:

Andrzej Skowron mainly investigates Rough set, Granular computing, Artificial intelligence, Theoretical computer science and Complex system. His research on Rough set concerns the broader Data mining. He has included themes like Complex adaptive system, Soft computing, Decision support system, Judgement and Computation in his Granular computing study.

In his research on the topic of Decision support system, Domain knowledge is strongly related with Interactive computation. His Artificial intelligence study integrates concerns from other disciplines, such as Machine learning and Natural language processing. He works mostly in the field of Complex system, limiting it down to concerns involving Intelligent decision support system and, occasionally, Theory of computation.

Between 2012 and 2020, his most popular works were:

  • Interactive granular computing (123 citations)
  • Interactive granular computing (123 citations)
  • Local rough set: A solution to rough data analysis in big data (50 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Programming language

His primary areas of study are Rough set, Granular computing, Artificial intelligence, Theoretical computer science and Complex system. Data mining covers he research in Rough set. His studies deal with areas such as Development and Decision support system as well as Granular computing.

His Artificial intelligence study incorporates themes from Machine learning, Information retrieval and Logical conjunction. His study in Theoretical computer science is interdisciplinary in nature, drawing from both Ontology, Inductive reasoning, Information system and Pattern recognition. As a member of one scientific family, Andrzej Skowron mostly works in the field of Complex system, focusing on Intelligent decision support system and, on occasion, Complex adaptive system and Business decision mapping.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Rudiments of rough sets

Zdziasław Pawlak;Andrzej Skowron.
Information Sciences (2007)

2766 Citations

The Discernibility Matrices and Functions in Information Systems

Andrzej Skowron;Cecylia Rauszer.
Intelligent Decision Support (1992)

2672 Citations

Rough sets: Some extensions

Zdzisław Pawlak;Andrzej Skowron.
Information Sciences (2007)

1628 Citations

Rough Sets in Knowledge Discovery 2

Lech Polkowski;Andrzej Skowron.
(1998)

1178 Citations

Foundations of Intelligent Systems

Zbigniew W. Ras;Andrzej Skowron;Qiuming Zhu;Z. Chen.
15th International Symposium ISMIS 2005, Saratoga Springs, NY, USA (1996)

1137 Citations

Rough sets and Boolean reasoning

Zdzisław Pawlak;Andrzej Skowron.
Information Sciences (2007)

1108 Citations

Rough Sets in Knowledge Discovery 2: Applications, Case Studies, and Software Systems

Lech Polkowski;J. Kacprzyk;A. Skowron.
(1998)

1102 Citations

Tolerance approximation spaces

Andrzej Skowron;Jaroslaw Stepaniuk.
Fundamenta Informaticae (1996)

1062 Citations

Rough set methods in feature selection and recognition

Roman W. Swiniarski;Andrzej Skowron.
Pattern Recognition Letters (2003)

961 Citations

Rough membership functions

Zdzisław Pawlak;Andrzej Skowron.
Advances in the Dempster-Shafer theory of evidence (1994)

536 Citations

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