Hierarchical Concept Learning by Fuzzy Semantic Cells

Concept modeling and learning have been important research topics in artificial intelligence and knowledge discovery. This paper studies a hierarchical concept learning method that requires a small amount of data to achieve competitive performances. The method starts from a set of fuzzy prototypes c...

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Autores principales:	Linna Zhu, Wei Li, Yongchuan Tang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	concept modeling fuzzy semantic cells prototypes prototype theory Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/bff9272806ac4a3c8eedeec081cad52c
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id	oai:doaj.org-article:bff9272806ac4a3c8eedeec081cad52c
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spelling	oai:doaj.org-article:bff9272806ac4a3c8eedeec081cad52c2021-11-25T16:36:32ZHierarchical Concept Learning by Fuzzy Semantic Cells10.3390/app1122107232076-3417https://doaj.org/article/bff9272806ac4a3c8eedeec081cad52c2021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/10723https://doaj.org/toc/2076-3417Concept modeling and learning have been important research topics in artificial intelligence and knowledge discovery. This paper studies a hierarchical concept learning method that requires a small amount of data to achieve competitive performances. The method starts from a set of fuzzy prototypes called Fuzzy Semantic Cells (FSCs). As a result of FSC parameter optimization, it creates a hierarchical structure of data–prototype–concept. Experiments are conducted to demonstrate the effectiveness of our approach in a classification problem. In particular, when faced with limited training data, our proposed method is comparable with traditional techniques in terms of robustness and generalization ability.Linna ZhuWei LiYongchuan TangMDPI AGarticleconcept modelingfuzzy semantic cellsprototypesprototype theoryTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10723, p 10723 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	concept modeling fuzzy semantic cells prototypes prototype theory Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	concept modeling fuzzy semantic cells prototypes prototype theory Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Linna Zhu Wei Li Yongchuan Tang Hierarchical Concept Learning by Fuzzy Semantic Cells
description	Concept modeling and learning have been important research topics in artificial intelligence and knowledge discovery. This paper studies a hierarchical concept learning method that requires a small amount of data to achieve competitive performances. The method starts from a set of fuzzy prototypes called Fuzzy Semantic Cells (FSCs). As a result of FSC parameter optimization, it creates a hierarchical structure of data–prototype–concept. Experiments are conducted to demonstrate the effectiveness of our approach in a classification problem. In particular, when faced with limited training data, our proposed method is comparable with traditional techniques in terms of robustness and generalization ability.
format	article
author	Linna Zhu Wei Li Yongchuan Tang
author_facet	Linna Zhu Wei Li Yongchuan Tang
author_sort	Linna Zhu
title	Hierarchical Concept Learning by Fuzzy Semantic Cells
title_short	Hierarchical Concept Learning by Fuzzy Semantic Cells
title_full	Hierarchical Concept Learning by Fuzzy Semantic Cells
title_fullStr	Hierarchical Concept Learning by Fuzzy Semantic Cells
title_full_unstemmed	Hierarchical Concept Learning by Fuzzy Semantic Cells
title_sort	hierarchical concept learning by fuzzy semantic cells
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/bff9272806ac4a3c8eedeec081cad52c
work_keys_str_mv	AT linnazhu hierarchicalconceptlearningbyfuzzysemanticcells AT weili hierarchicalconceptlearningbyfuzzysemanticcells AT yongchuantang hierarchicalconceptlearningbyfuzzysemanticcells
_version_	1718413100399460352

Hierarchical Concept Learning by Fuzzy Semantic Cells

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