What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Machine learning
Benedetto Matarazzo mainly investigates Rough set, Dominance-based rough set approach, Decision rule, Data mining and Multicriteria classification.
His work in Rough set addresses issues such as Binary relation, which are connected to fields such as Transitive relation, Fuzzy set and Weighted product model.
His Dominance-based rough set approach research is multidisciplinary, incorporating elements of Algorithm and Decision analysis.
Benedetto Matarazzo has included themes like Preference, Decision problem and Rule of inference in his Decision rule study.
His research integrates issues of Generalization and Bayesian probability in his study of Data mining.
His studies deal with areas such as Bankruptcy risk and Theoretical computer science as well as Multicriteria classification.
His most cited work include:
- Rough sets theory for multicriteria decision analysis (1265 citations)
- Rough approximation of a preference relation by dominance relations (411 citations)
- Rough approximation by dominance relations (339 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Rough set, Dominance-based rough set approach, Decision rule, Artificial intelligence and Mathematical optimization.
His Rough set study deals with the bigger picture of Data mining.
His study on Dominance-based rough set approach also encompasses disciplines like
- Theoretical computer science which intersects with area such as Binary relation,
- Algorithm, which have a strong connection to Generalization.
His study in Decision rule is interdisciplinary in nature, drawing from both Decision tree, Optimal decision, Decision problem and Decision analysis.
His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning and Stochastic dominance.
His Mathematical optimization study incorporates themes from Sorting and Choquet integral, Fuzzy logic.
He most often published in these fields:
- Rough set (60.75%)
- Dominance-based rough set approach (56.07%)
- Decision rule (43.93%)
What were the highlights of his more recent work (between 2010-2021)?
- Rough set (60.75%)
- Dominance-based rough set approach (56.07%)
- Decision rule (43.93%)
In recent papers he was focusing on the following fields of study:
Benedetto Matarazzo mostly deals with Rough set, Dominance-based rough set approach, Decision rule, Computational intelligence and Artificial intelligence.
His work carried out in the field of Rough set brings together such families of science as Vagueness, Probabilistic logic and Lattice.
His Decision rule research is multidisciplinary, incorporating elements of Decision analysis, Multi-objective optimization, Multiple-criteria decision analysis, Mathematical optimization and Decision model.
His Computational intelligence study also includes
- Management science and related Multicriteria decision, Finance and Actuarial science,
- Data science which connect with Financial engineering, Missing data, Financial risk and Knowledge extraction,
- Operations research and related Transport engineering, Aggregate, Decision problem and Choquet integral.
His work on Variety as part of general Artificial intelligence research is often related to Focus, thus linking different fields of science.
He interconnects Preference, Preference learning, Preference relation, Pairwise comparison and Equivalence relation in the investigation of issues within Machine learning.
Between 2010 and 2021, his most popular works were:
- The Choquet integral with respect to a level dependent capacity (66 citations)
- jMAF - Dominance-Based Rough Set Data Analysis Framework (47 citations)
- Stochastic multi-attribute acceptability analysis (SMAA): an application to the ranking of Italian regions (44 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Machine learning
Benedetto Matarazzo mainly focuses on Decision rule, Rough set, Dominance-based rough set approach, Artificial intelligence and Multiple-criteria decision analysis.
His Data mining research extends to the thematically linked field of Decision rule.
His Rough set study integrates concerns from other disciplines, such as Consistency, Data analysis and Extension.
His work deals with themes such as Decision tree, Operations research and Decision analysis, which intersect with Dominance-based rough set approach.
His Decision analysis research includes themes of Decision support system, Transport engineering and Decision problem.
His Multiple-criteria decision analysis research integrates issues from Multi-objective optimization, Probabilistic logic and Sample.
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