Classification and Value Assessment of Sports Intangible Cultural Heritage Resources Combined with Digital Technology
This paper is dedicated to designing and constructing a knowledge ontology framework for sports intangible cultural heritage (ICH) resources, aiming to support their preservation and inheritance by integrating and mining sports ICH resources. The study includes the collection of multiple data of spo...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Sciendo
2024-01-01
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| Series: | Applied Mathematics and Nonlinear Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/amns-2024-0548 |
| _version_ | 1797279162684145664 |
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| author | Zhang Yongjiang Ala Tengcang |
| author_facet | Zhang Yongjiang Ala Tengcang |
| author_sort | Zhang Yongjiang |
| collection | DOAJ |
| description | This paper is dedicated to designing and constructing a knowledge ontology framework for sports intangible cultural heritage (ICH) resources, aiming to support their preservation and inheritance by integrating and mining sports ICH resources. The study includes the collection of multiple data of sports ICH from various data sources, and constructing ICH knowledge ontology using CIDOC CRM metadata reference model and seven-step method. To enrich the content of the ontology, the TextRank algorithm is used to extract textual critical information and design a domain-specific NER model for sports NRL. In addition, the study adopts the VSM vector space model for text representation and uses an improved hierarchical classification model for text categorization to improve classification accuracy. The study also explores the similarity calculation of concepts in the sports NRM ontology and proposes a semantic similarity calculation formula based on the ontology concepts. Respondents’ willingness to pay was investigated through the conditional value method (CVM) to assess the value of sports NRM tourism resources. Finally, the influencing factors of respondents’ willingness to pay were analyzed using statistical analysis and Logistic regression model, and it was found that they were mainly influenced by the degree of understanding of sports non-heritage resources and the level of education. The results of this study not only provide theoretical and methodological support for the effective integration and excavation of sports non-heritage resources and a new perspective for their protection, inheritance and sustainable development. |
| first_indexed | 2024-03-07T16:20:18Z |
| format | Article |
| id | doaj.art-f8e953de6ad047909091b7b90a8779d4 |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-07T16:20:18Z |
| publishDate | 2024-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-f8e953de6ad047909091b7b90a8779d42024-03-04T07:30:42ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns-2024-0548Classification and Value Assessment of Sports Intangible Cultural Heritage Resources Combined with Digital TechnologyZhang Yongjiang0Ala Tengcang11Ordos Institute of Technology, Ordos, Inner Mongolia, 017000, China.1Ordos Institute of Technology, Ordos, Inner Mongolia, 017000, China.This paper is dedicated to designing and constructing a knowledge ontology framework for sports intangible cultural heritage (ICH) resources, aiming to support their preservation and inheritance by integrating and mining sports ICH resources. The study includes the collection of multiple data of sports ICH from various data sources, and constructing ICH knowledge ontology using CIDOC CRM metadata reference model and seven-step method. To enrich the content of the ontology, the TextRank algorithm is used to extract textual critical information and design a domain-specific NER model for sports NRL. In addition, the study adopts the VSM vector space model for text representation and uses an improved hierarchical classification model for text categorization to improve classification accuracy. The study also explores the similarity calculation of concepts in the sports NRM ontology and proposes a semantic similarity calculation formula based on the ontology concepts. Respondents’ willingness to pay was investigated through the conditional value method (CVM) to assess the value of sports NRM tourism resources. Finally, the influencing factors of respondents’ willingness to pay were analyzed using statistical analysis and Logistic regression model, and it was found that they were mainly influenced by the degree of understanding of sports non-heritage resources and the level of education. The results of this study not only provide theoretical and methodological support for the effective integration and excavation of sports non-heritage resources and a new perspective for their protection, inheritance and sustainable development.https://doi.org/10.2478/amns-2024-0548vector space modellogistic regression modelhierarchical classification modelsemantic similaritynon-heritage resources94a08 |
| spellingShingle | Zhang Yongjiang Ala Tengcang Classification and Value Assessment of Sports Intangible Cultural Heritage Resources Combined with Digital Technology Applied Mathematics and Nonlinear Sciences vector space model logistic regression model hierarchical classification model semantic similarity non-heritage resources 94a08 |
| title | Classification and Value Assessment of Sports Intangible Cultural Heritage Resources Combined with Digital Technology |
| title_full | Classification and Value Assessment of Sports Intangible Cultural Heritage Resources Combined with Digital Technology |
| title_fullStr | Classification and Value Assessment of Sports Intangible Cultural Heritage Resources Combined with Digital Technology |
| title_full_unstemmed | Classification and Value Assessment of Sports Intangible Cultural Heritage Resources Combined with Digital Technology |
| title_short | Classification and Value Assessment of Sports Intangible Cultural Heritage Resources Combined with Digital Technology |
| title_sort | classification and value assessment of sports intangible cultural heritage resources combined with digital technology |
| topic | vector space model logistic regression model hierarchical classification model semantic similarity non-heritage resources 94a08 |
| url | https://doi.org/10.2478/amns-2024-0548 |
| work_keys_str_mv | AT zhangyongjiang classificationandvalueassessmentofsportsintangibleculturalheritageresourcescombinedwithdigitaltechnology AT alatengcang classificationandvalueassessmentofsportsintangibleculturalheritageresourcescombinedwithdigitaltechnology |