A Chinese Knowledge Graph Dataset in the Field of Scientific Fitness
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AG8WCI8Y6" target="_blank" >RIV/00216208:11320/26:G8WCI8Y6 - isvavai.cz</a>
Result on the web
<a href="https://www.nature.com/articles/s41597-025-04519-6" target="_blank" >https://www.nature.com/articles/s41597-025-04519-6</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1038/s41597-025-04519-6" target="_blank" >10.1038/s41597-025-04519-6</a>
Alternative languages
Result language
angličtina
Original language name
A Chinese Knowledge Graph Dataset in the Field of Scientific Fitness
Original language description
To promote the development of scientific fitness research and practice, we propose the Chinese Knowledge Graph Dataset in the Field of Scientific Fitness (FitKG-CN). This knowledge graph contains over 10,000 fitness-related terms, categorized into eight main groups: body parts, items of exercise, fitness movement, equipment and tools, exercise goals, anatomical structures, nutrients, and technical terms. The construction of FitKG-CN is based on authoritative data sources, undergoing rigorous preprocessing, including noise removal, format standardization, and normalization of entities and relationships. The data is manually annotated on a professional platform and ultimately stored in a Neo4j graph database for visualization. Additionally, we trained a Chinese SpERT model using the manually annotated data to enhance the automation of data processing. The experimental results show that the model achieved an F1 score of 94.05% in entity recognition tasks and 82.00% in relation extraction tasks, validating the effectiveness of the model and improving the scalability of the dataset.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
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Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Scientific Data
ISSN
2052-4463
e-ISSN
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Volume of the periodical
12
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
30
Pages from-to
205
UT code for WoS article
001413333200005
EID of the result in the Scopus database
2-s2.0-85217989010