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Knowledge graph of alpine skiing events: A focus on meteorological conditions
Alpine skiing, as an outdoor winter sport, is particularly vulnerable to the variation of meteorological conditions. Scattered and multi-source big data cannot be fully utilized to conduct effective decision analyses by conventional data analysis methods. Presently, knowledge graphs are the most adv...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9491590/ https://www.ncbi.nlm.nih.gov/pubmed/36129923 http://dx.doi.org/10.1371/journal.pone.0274164 |
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author | Tang, Wei Zhang, Xueying Feng, Deen Wang, Yipeng Ye, Peng Qu, Hanhua |
author_facet | Tang, Wei Zhang, Xueying Feng, Deen Wang, Yipeng Ye, Peng Qu, Hanhua |
author_sort | Tang, Wei |
collection | PubMed |
description | Alpine skiing, as an outdoor winter sport, is particularly vulnerable to the variation of meteorological conditions. Scattered and multi-source big data cannot be fully utilized to conduct effective decision analyses by conventional data analysis methods. Presently, knowledge graphs are the most advanced organization form of knowledge base, which can make explicit the complex relationships among different objects. Thus, introducing knowledge graph to the event management of alpine skiing is significant to improve the ability of risk prediction and decision-making. In this research, we analyze the components and dynamic characteristics of alpine skiing, and construct an “Object-Characteristic-Relation” representation model to express multi-level knowledge. Moreover, we propose a “Characteristic-value- Relationship” representation method based on the multi-source data, to construct the knowledge graph of alpine skiing. With the proposed method, comprehensive relationships between meteorological conditions and alpine skiing can be represented clearly, and support further knowledge reasoning for the event management under meteorological conditions. We have tested the utility of the proposed method in a case study of 2018 Winter Olympics in PyeongChang. The case study realizes an semi-automatic construction of knowledge graph for alpine skiing, provides decision supports for event risk managements, according to different meteorological conditions, and grounds a foundation for future knowledge graph construction of other large-scale sport events. |
format | Online Article Text |
id | pubmed-9491590 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-94915902022-09-22 Knowledge graph of alpine skiing events: A focus on meteorological conditions Tang, Wei Zhang, Xueying Feng, Deen Wang, Yipeng Ye, Peng Qu, Hanhua PLoS One Research Article Alpine skiing, as an outdoor winter sport, is particularly vulnerable to the variation of meteorological conditions. Scattered and multi-source big data cannot be fully utilized to conduct effective decision analyses by conventional data analysis methods. Presently, knowledge graphs are the most advanced organization form of knowledge base, which can make explicit the complex relationships among different objects. Thus, introducing knowledge graph to the event management of alpine skiing is significant to improve the ability of risk prediction and decision-making. In this research, we analyze the components and dynamic characteristics of alpine skiing, and construct an “Object-Characteristic-Relation” representation model to express multi-level knowledge. Moreover, we propose a “Characteristic-value- Relationship” representation method based on the multi-source data, to construct the knowledge graph of alpine skiing. With the proposed method, comprehensive relationships between meteorological conditions and alpine skiing can be represented clearly, and support further knowledge reasoning for the event management under meteorological conditions. We have tested the utility of the proposed method in a case study of 2018 Winter Olympics in PyeongChang. The case study realizes an semi-automatic construction of knowledge graph for alpine skiing, provides decision supports for event risk managements, according to different meteorological conditions, and grounds a foundation for future knowledge graph construction of other large-scale sport events. Public Library of Science 2022-09-21 /pmc/articles/PMC9491590/ /pubmed/36129923 http://dx.doi.org/10.1371/journal.pone.0274164 Text en © 2022 Tang et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Tang, Wei Zhang, Xueying Feng, Deen Wang, Yipeng Ye, Peng Qu, Hanhua Knowledge graph of alpine skiing events: A focus on meteorological conditions |
title | Knowledge graph of alpine skiing events: A focus on meteorological conditions |
title_full | Knowledge graph of alpine skiing events: A focus on meteorological conditions |
title_fullStr | Knowledge graph of alpine skiing events: A focus on meteorological conditions |
title_full_unstemmed | Knowledge graph of alpine skiing events: A focus on meteorological conditions |
title_short | Knowledge graph of alpine skiing events: A focus on meteorological conditions |
title_sort | knowledge graph of alpine skiing events: a focus on meteorological conditions |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9491590/ https://www.ncbi.nlm.nih.gov/pubmed/36129923 http://dx.doi.org/10.1371/journal.pone.0274164 |
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