Concept-cognitive learning survey: Mining and fusing knowledge from data

D Guo, W Xu, W Ding, Y Yao, X Wang, W Pedrycz… - Information …, 2024 - Elsevier
Abstract Concept-cognitive learning (CCL), an emerging intelligence learning paradigm, has
recently become a popular research subject in artificial intelligence and cognitive …

M-FCCL: Memory-based concept-cognitive learning for dynamic fuzzy data classification and knowledge fusion

D Guo, W Xu, Y Qian, W Ding - Information Fusion, 2023 - Elsevier
Abstract Concept-cognitive learning (CCL) is an emerging field for studying the
representation and processing of knowledge embedded in data. Many efforts are focused on …

Fuzzy-granular concept-cognitive learning via three-way decision: performance evaluation on dynamic knowledge discovery

D Guo, W Xu, Y Qian, W Ding - IEEE transactions on fuzzy …, 2023 - ieeexplore.ieee.org
Concept-cognitive learning (CCL) and three-way decision (3WD) models provide powerful
techniques for knowledge discovery. Some early attempts in the field have successfully …

Two-way concept-cognitive learning via concept movement viewpoint

W Xu, D Guo, J Mi, Y Qian, K Zheng… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Representation and learning of concepts are critical problems in data science and cognitive
science. However, the existing research about concept learning has one prevalent …

Fuzzy-based concept-cognitive learning: An investigation of novel approach to tumor diagnosis analysis

D Guo, W Xu - Information Sciences, 2023 - Elsevier
Medical decision-making with high-dimensional complex data has recently become a focus
and difficulty in artificial intelligence and the medical field. Tumor diagnosis using data …

Data-driven quantification and intelligent decision-making in traditional Chinese medicine: a review

X Chu, S Wu, B Sun, Q Huang - International Journal of Machine Learning …, 2024 - Springer
Traditional Chinese medicine (TCM) originates from the practical experience of human
beings' constant struggle with nature. In five thousand years, TCM has gradually risen from …

Feature selection using zentropy-based uncertainty measure

K Yuan, D Miao, Y Yao, H Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Feature selection and entropy theory are two efficacious data analysis tools for investigating
uncertainty information processing in artificial intelligence. The fruitful marriage of the two …

Ze-HFS: Zentropy-based uncertainty measure for heterogeneous feature selection and knowledge discovery

K Yuan, D Miao, W Pedrycz, W Ding… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Knowledge discovery of heterogeneous data is an active topic in knowledge engineering.
Feature selection for heterogeneous data is an important part of effective data analysis …

A local rough set method for feature selection by variable precision composite measure

K Yuan, W Xu, D Miao - Applied Soft Computing, 2024 - Elsevier
Feature selection using variable precision neighborhood rough sets (VPNRS) has garnered
considerable attention in data mining and knowledge discovery. Nevertheless, the positive …

Correlation concept-cognitive learning model for multi-label classification

J Wu, ECC Tsang, W Xu, C Zhang, L Yang - Knowledge-Based Systems, 2024 - Elsevier
As a cognitive process, concept-cognitive learning (CCL) emphasizes the structured
expression of data through systematic cognition and understanding, to obtain valuable …