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

<p>The article explores the value mining of big data in the intelligent transformation of tourism through the construction and practice of tourism big data intelligent evaluation index system. At the same time, it has done extensive research on specific intelligence methods and developed a range of models and algorithms that have practical application value. Firstly, the entropy weight method is used to evaluate the measurement, obtain the corresponding information entropy, and quantify the difference in the degree of information contained in the index system. Then, according to the principle of scientific and collectability of the indicator system, scholars formulate the indicator system from the three levels of tourism demand, tourism supply, and tourism support by drawing on the relevant literature review so as to construct the evaluation indicator system and measure the overall development level of tourism. Finally, specific methods for tourism intelligence are listed and recommended, including the release of tourists’ behavioral data through a data access processing module and persistent storage. As well as collecting buried records, we aim to understand the tourists’ preferences. According to the experimental analysis, the Tourism resource level experienced a multiplicative increase of 2.85 from 3.25 to 6.1 in 2019. gxlljw66 tourists reached the maximum value of 8 on the number of transactions, bamull123. Although it was higher than gxlljw66 tourists on the Number of transactions is slightly less than that of gxlljw66, its overall value is also very good. These values verify the important role of big data technology in tourism and provide a useful reference for the development of intelligent tourism transformation.</p>
</abstract>

The article explores the value mining of big data in the intelligent transformation of tourism through the construction and practice of tourism big data intelligent evaluation index system. At the same time, it has done extensive research on specific intelligence methods and developed a range of models and algorithms that have practical application value. Firstly, the entropy weight method is used to evaluate the measurement, obtain the corresponding information entropy, and quantify the difference in the degree of information contained in the index system. Then, according to the principle of scientific and collectability of the indicator system, scholars formulate the indicator system from the three levels of tourism demand, tourism supply, and tourism support by drawing on the relevant literature review so as to construct the evaluation indicator system and measure the overall development level of tourism. Finally, specific methods for tourism intelligence are listed and recommended, including the release of tourists’ behavioral data through a data access processing module and persistent storage. As well as collecting buried records, we aim to understand the tourists’ preferences. According to the experimental analysis, the Tourism resource level experienced a multiplicative increase of 2.85 from 3.25 to 6.1 in 2019. gxlljw66 tourists reached the maximum value of 8 on the number of transactions, bamull123. Although it was higher than gxlljw66 tourists on the Number of transactions is slightly less than that of gxlljw66, its overall value is also very good. These values verify the important role of big data technology in tourism and provide a useful reference for the development of intelligent tourism transformation.

An Exploration of Tourism’s Intelligent Transformation and Development Driven by Big Data

Applied Mathematics and Nonlinear Sciences

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

The article explores the value mining of big data in the intelligent transformation of tourism through the construction and practice of tourism big data...

An Exploration of Tourism’s Intelligent Transformation and Development Driven by Big Data

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 21. Apr. 2024

Akzeptiert: 09. Juli 2024

DOI: https://doi.org/10.2478/amns-2024-2024

Schlüsselwörter
Entropy power method, Tourism, Behavioral data, Smart transformation

© 2024 Haibin Chen., published by Sciendo

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

An Exploration of Tourism’s Intelligent Transformation and Development Driven by Big Data

Online veröffentlicht: 05. Aug. 2024

Seitenbereich: -

Eingereicht: 21. Apr. 2024

Akzeptiert: 09. Juli 2024

DOI: https://doi.org/10.2478/amns-2024-2024

SchlüsselwörterEntropy power method, Tourism, Behavioral data, Smart transformation

© 2024 Haibin Chen., published by Sciendo

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

Schlüsselwörter
Entropy power method, Tourism, Behavioral data, Smart transformation