Innovative Research on the Dissemination of Intangible Cultural Heritage and Tourism Development in Shaanxi Province Driven by Data

Authors

  • Xingru Liu
  • Lingling Cui
  • Ziqi Wang
  • Yueyi Wang
  • Meijuan Shan

DOI:

https://doi.org/10.54097/v6hx6g16

Keywords:

Intangible Cultural Heritage, Qingxing Travel APP, K-means Clustering, Apriori Algorithm

Abstract

With the strengthening of the state’s protection policies for intangible cultural heritage, the importance of intangible cultural heritage has become increasingly prominent. However, the attention paid to intangible cultural heritage in the field of tourism remains relatively low. Based on the data of intangible cultural heritage in Shaanxi Province, this paper analyzes the current situation and potential value of intangible cultural heritage through the application of visualization techniques, K-means clustering, and the Apriori algorithm. For this purpose, the concept of the Qingxing Travel APP is proposed to meet people’s tourism needs in a brand-new way of traveling, while achieving the effect of promoting tourism with culture and promoting culture with tourism.

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References

[1] Qi Yukun. Intangible in the new era to glow the new vitality [N]. People's Daily, 2024-10-31 (011). DOI: 10.28655 / n.c. Nki NRMRB. 2024.012425.

[2] Niu Jiaxin. Inheriting intangible cultural heritage skills to light up a better life [N]. China Tourism News,2024-11-05(002).

[3] WANG Sen, Liu Chen, XING Shuaijie. K means clustering algorithm study review [J]. Journal of east China jiaotong university, 2022, 33 (5): 6, 119-126. The DOI: 10.16749 / j. carol carroll nki jecjtu. 20220914.001.

[4] Lu Lina, Chen Yaping, WEI Hengyi, et al. Research on Apriori algorithm in Mining association rules [J]. Small Microcomputer Systems, 2000, (09):940-943.

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Published

28-11-2024

Issue

Section

Articles

How to Cite

Liu, X., Cui, L., Wang, Z., Wang, Y., & Shan, M. (2024). Innovative Research on the Dissemination of Intangible Cultural Heritage and Tourism Development in Shaanxi Province Driven by Data. Academic Journal of Management and Social Sciences, 9(2), 234-238. https://doi.org/10.54097/v6hx6g16