Visual analysis of knowledge graph based on fuzzy sets in Chinese martial arts routines
There are many schools of Chinese martial arts routines and complex movements; research on this topic is more geared toward Taijiquan (a kind of traditional Chinese shadow boxing), which is a more well-known type of martial arts. Therefore, the purpose of this paper is to visually analyze the resear...
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| Format: | Article |
| Language: | English |
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AIMS Press
2023-05-01
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| Series: | AIMS Mathematics |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/math.2023940?viewType=HTML |
| _version_ | 1827928371443531776 |
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| author | Jun Jiang Junjie Lv Muhammad Bilal Khan |
| author_facet | Jun Jiang Junjie Lv Muhammad Bilal Khan |
| author_sort | Jun Jiang |
| collection | DOAJ |
| description | There are many schools of Chinese martial arts routines and complex movements; research on this topic is more geared toward Taijiquan (a kind of traditional Chinese shadow boxing), which is a more well-known type of martial arts. Therefore, the purpose of this paper is to visually analyze the research of Chinese martial arts routines based on the knowledge graph method and to propose a knowledge graph method based on the fuzzy set theory, which is called the transF model throughout this paper. The transF model used the fuzzy relational operation of vectors to not only reduce the computational complexity, but to also better integrate multi-dimensional data, especially when the training set is not particularly sufficient. For the visual analysis of Chinese martial arts routines, this paper selected the 16-year data from 2005 to 2020 as the analysis sample, analyzed high-yield institutions and high-yield authors, and conducted a centrality analysis of the whole dataset. From the structure of the knowledge graph, traditional martial arts are the core part of Chinese martial arts, with a centrality of 0.14. Competitive martial arts are the main branch of Chinese martial arts and the third core after Tai Chi and traditional martial arts, with a centrality of 0.41, which is higher than that of traditional martial arts. This shows its importance in martial arts research. |
| first_indexed | 2024-03-13T06:06:47Z |
| format | Article |
| id | doaj.art-df51f386a03047afaf76f48cb1a6c89d |
| institution | Directory Open Access Journal |
| issn | 2473-6988 |
| language | English |
| last_indexed | 2024-03-13T06:06:47Z |
| publishDate | 2023-05-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Mathematics |
| spelling | doaj.art-df51f386a03047afaf76f48cb1a6c89d2023-06-12T01:42:41ZengAIMS PressAIMS Mathematics2473-69882023-05-0188184911851110.3934/math.2023940Visual analysis of knowledge graph based on fuzzy sets in Chinese martial arts routinesJun Jiang0Junjie Lv1Muhammad Bilal Khan21. Institute of Physical Education and Health, Yulin Normal University, Yulin 537000, China1. Institute of Physical Education and Health, Yulin Normal University, Yulin 537000, China2. Department of Mathematics, COMSATS University Islamabad, Islamabad 4400, PakistanThere are many schools of Chinese martial arts routines and complex movements; research on this topic is more geared toward Taijiquan (a kind of traditional Chinese shadow boxing), which is a more well-known type of martial arts. Therefore, the purpose of this paper is to visually analyze the research of Chinese martial arts routines based on the knowledge graph method and to propose a knowledge graph method based on the fuzzy set theory, which is called the transF model throughout this paper. The transF model used the fuzzy relational operation of vectors to not only reduce the computational complexity, but to also better integrate multi-dimensional data, especially when the training set is not particularly sufficient. For the visual analysis of Chinese martial arts routines, this paper selected the 16-year data from 2005 to 2020 as the analysis sample, analyzed high-yield institutions and high-yield authors, and conducted a centrality analysis of the whole dataset. From the structure of the knowledge graph, traditional martial arts are the core part of Chinese martial arts, with a centrality of 0.14. Competitive martial arts are the main branch of Chinese martial arts and the third core after Tai Chi and traditional martial arts, with a centrality of 0.41, which is higher than that of traditional martial arts. This shows its importance in martial arts research.https://www.aimspress.com/article/doi/10.3934/math.2023940?viewType=HTMLchinese martial arts routinesvisual analysisknowledge graphfuzzy set theorymartial arts routine visualization |
| spellingShingle | Jun Jiang Junjie Lv Muhammad Bilal Khan Visual analysis of knowledge graph based on fuzzy sets in Chinese martial arts routines AIMS Mathematics chinese martial arts routines visual analysis knowledge graph fuzzy set theory martial arts routine visualization |
| title | Visual analysis of knowledge graph based on fuzzy sets in Chinese martial arts routines |
| title_full | Visual analysis of knowledge graph based on fuzzy sets in Chinese martial arts routines |
| title_fullStr | Visual analysis of knowledge graph based on fuzzy sets in Chinese martial arts routines |
| title_full_unstemmed | Visual analysis of knowledge graph based on fuzzy sets in Chinese martial arts routines |
| title_short | Visual analysis of knowledge graph based on fuzzy sets in Chinese martial arts routines |
| title_sort | visual analysis of knowledge graph based on fuzzy sets in chinese martial arts routines |
| topic | chinese martial arts routines visual analysis knowledge graph fuzzy set theory martial arts routine visualization |
| url | https://www.aimspress.com/article/doi/10.3934/math.2023940?viewType=HTML |
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