<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Under the background of big data, how to better promote the development and protection of folklore sports tourism resources under the management of rural revitalization strategy is the important research direction of this paper. This paper is based on the data mining method of clustering analysis under big data technology, which is realized by constructing a clustering feature tree, i.e., a CF tree. Next, formal clustering under unguided data mining is introduced. Combined with the folk sports tourism market in Langxia town, the development of folk sports tourism in Langxia town under the management of rural revitalization strategy is analyzed to lay the foundation for further folk sports tourism resources development and protection strategies. The analysis results show that 45.8% of the tourists participating in rural folk sports tourism are male and 54.2% are female; in terms of age composition, tourists aged 18-59 account for 93.5% of the total; in terms of income level, the middle and high-end tourist population accounts for 32%; in terms of education, 65% of the tourists’ cultural level is undergraduate or specialist. Regarding the characteristics of tourists’ travel behavior, the mode of travel is mainly self-driving; the largest proportion of tourists choose to travel with their families, and the per capita consumption expenditure is below 200 yuan. Under the management of the rural revitalization strategy, the main target groups of folklore characteristic sports tourist attractions should be women, middle-aged and middle-aged people, with higher education levels, and higher incomes.</p>
</abstract>

Under the background of big data, how to better promote the development and protection of folklore sports tourism resources under the management of rural revitalization strategy is the important research direction of this paper. This paper is based on the data mining method of clustering analysis under big data technology, which is realized by constructing a clustering feature tree, i.e., a CF tree. Next, formal clustering under unguided data mining is introduced. Combined with the folk sports tourism market in Langxia town, the development of folk sports tourism in Langxia town under the management of rural revitalization strategy is analyzed to lay the foundation for further folk sports tourism resources development and protection strategies. The analysis results show that 45.8% of the tourists participating in rural folk sports tourism are male and 54.2% are female; in terms of age composition, tourists aged 18-59 account for 93.5% of the total; in terms of income level, the middle and high-end tourist population accounts for 32%; in terms of education, 65% of the tourists’ cultural level is undergraduate or specialist. Regarding the characteristics of tourists’ travel behavior, the mode of travel is mainly self-driving; the largest proportion of tourists choose to travel with their families, and the per capita consumption expenditure is below 200 yuan. Under the management of the rural revitalization strategy, the main target groups of folklore characteristic sports tourist attractions should be women, middle-aged and middle-aged people, with higher education levels, and higher incomes.

Analysis of Folklore Sports Tourism Resources Development and Protection Strategies under the Management of Rural Revitalization Strategy in the Background of Big Data

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Under the background of big data, how to better promote the development and protection of folklore sports tourism resources under the management of rural...

Analysis of Folklore Sports Tourism Resources Development and Protection Strategies under the Management of Rural Revitalization Strategy in the Background of Big Data

Data publikacji: 21 lip 2023

Zakres stron: -

Otrzymano: 19 lut 2022

Przyjęty: 28 wrz 2022

DOI: https://doi.org/10.2478/amns.2023.2.00066

Słowa kluczowe
Cluster analysis, Rural revitalization strategy, Folkloric sports activities, Tourism resource conservation

© 2023 Yin Ma et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Analysis of Folklore Sports Tourism Resources Development and Protection Strategies under the Management of Rural Revitalization Strategy in the Background of Big Data

Data publikacji: 21 lip 2023

Zakres stron: -

Otrzymano: 19 lut 2022

Przyjęty: 28 wrz 2022

DOI: https://doi.org/10.2478/amns.2023.2.00066

Słowa kluczoweCluster analysis, Rural revitalization strategy, Folkloric sports activities, Tourism resource conservation

© 2023 Yin Ma et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Słowa kluczowe
Cluster analysis, Rural revitalization strategy, Folkloric sports activities, Tourism resource conservation