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

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.

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