Research summary
Contributions span fuzzy linguistic modeling, evolutionary and ensemble learning, and bibliometric tooling. A 2-tuple fuzzy linguistic representation model was introduced to overcome information loss in linguistic aggregation by pairing a linguistic term with a numeric value in (-0.5, 0.5), providing a continuous representation that supports fusion operations on linguistic information [3]. This line was extended with hesitant fuzzy linguistic term sets, allowing experts to express judgments via several linguistic terms or richer constructions when a single term is insufficient, applied to decision-making contexts where hesitation is qualitative rather than purely quantitative [5]. For learning from imbalanced data, an ensemble review classified bagging-, boosting-, and hybrid-based approaches and analyzed how ensemble structure must be designed specifically to address class imbalance rather than relying on single-classifier accuracy gains [2]. A retrospective on the SMOTE preprocessing algorithm at its 15-year mark assessed its role as a de facto standard for imbalanced learning, its extensions into multilabel, incremental, semi-supervised, and multi-instance settings, and the open challenges arising from large-scale data and concept drift [6]. The KEEL open-source platform for evolutionary learning and soft-computing data mining was described with three additions: the KEEL-dataset repository of partitioned datasets with reference results, guidelines for integrating new algorithms, and an experimental analysis framework supporting regression, classification, clustering, and pattern mining [4]. A separate review compared science mapping software tools, examining the bibliometric techniques and analysis types each supports, framed as a guide for selecting tools for conceptual, intellectual, and social structure analysis of research domains [1].
Recent publications
- Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AIDOI
- A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithmsDOI
- Science mapping software tools: Review, analysis, and cooperative study among toolsDOI
- A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based ApproachesDOI
- A 2-tuple fuzzy linguistic representation model for computing with wordsDOI
- An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory fieldDOI
- KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework
- Hesitant Fuzzy Linguistic Term Sets for Decision MakingDOI
- Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of powerDOI
- SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year AnniversaryDOI
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External profiles
- ORCID: https://orcid.org/0000-0002-7283-312X
- OpenAlex: openalex.org
Profile compiled from public sources (Researchmap, OpenAlex, Kumamoto University faculty directory). Last refreshed 2026-05. Report incorrect information.