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A novel scenic spots assessment and recommendation method based on network attention: augmented mining model using probabilistic linguistic term set combined with VIKOR

Yuyan Luo (College of Management Science, Chengdu University of Technology, Chengdu, China)
Xiaojing Yu (College of Management Science, Chengdu University of Technology, Chengdu, China)
Fei Xie (National Minorities' Culture Research Institute, Dali University, Dali, China)
Zheng Yang (College of Management Science, Chengdu University of Technology, Chengdu, China)
Jun Wang (Business School, Sichuan Normal University, Chengdu, China)

Kybernetes

ISSN: 0368-492X

Article publication date: 9 June 2023

Issue publication date: 30 October 2024

91

Abstract

Purpose

The purpose is to provide decision support for tourists recommending scenic spots and corresponding suggestions for the management of scenic spots.

Design/methodology/approach

Based on the Baidu index data generated, this paper analyzes the temporal and spatial characteristics of network attention of 5A scenic spots in Sichuan Province. The online comment data are used to build the assessment model of scenic spots based on network attention, and the comment information of tourists is mined and analyzed through statistical analysis. At the same time, the key attributes of scenic spots from the perspective of network attention are evaluated and analyzed by using the probabilistic linguistic term set. Finally, this paper further constructs a recommendation model based on the key attribute set of scenic spots.

Findings

This paper uses different types of tourism network information, integrates multi-types of data and methods, fully excavates the value information of tourism network information, constructs the research framework of “scenic spot assessment + scenic spot recommendation” from the perspective of network attention, analyzes the network attention characteristics of scenic spots, evaluates the performance of scenic spots, and implements scenic spot recommendation.

Originality/value

This paper integrates multi-source data and multidisciplinary theoretical methods to form a scenic spot research framework of “assessment + recommendation” from the perspective of network attention.

Keywords

Acknowledgements

This research was funded by the Humanities and Social Sciences Program of the Ministry of Education of the People's Republic of China (Grant No. 20YJC630095), the National Natural Science Foundation of China (Grant No. 71971151), Key Project of Research Center for Systems Science and Enterprise Development (Grant No. Xq21B04), General Project of Research Center for Science and Technology Innovation and New Economy in Chengdu-Chongqing Economic Circle (Grant No. CYCX2021YB08), Key Project of Sichuan Leisure Sports Industry Development and Research Center (Grant No. XXTYCY2021A01), Philosophy and Social Science Research Foundation of Chengdu University of Technology (Grant No. YJ2021-YB002), General Project of Research Center for Sichuan Disaster Economy (Grant No. ZHJJ2021-YB001) and General Project of Western Ecological Civilization Research Center (Grant No. XBST2021-YB001).

Citation

Luo, Y., Yu, X., Xie, F., Yang, Z. and Wang, J. (2024), "A novel scenic spots assessment and recommendation method based on network attention: augmented mining model using probabilistic linguistic term set combined with VIKOR", Kybernetes, Vol. 53 No. 10, pp. 3774-3797. https://doi.org/10.1108/K-12-2022-1682

Publisher

:

Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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