Personalised recommendation of regional tourism routes based on weighted matrix factorisation

In order to improve the recommendation accuracy and scenic spot coverage of tourism route recommendation methods, this paper proposes a new regional tourism routes personalised recommendation method based on weighted matrix factorisation.Firstly, according to the frequent tourism location sequence, the user tourism preference model is constructed to mine the user tourism preference.Secondly, from the two aspects of influence weight and time weight of tourist attractions, the weighted scoring matrix of tourist attractions is constructed.Finally, the weighted matrix is dimensionally reduced by using the matrix factorisation method, and the prediction scoring matrix is constructed to score the scenic spots in the scenic spots collection, and the top N scenic spots with higher scores are recommended to users as personalised tourist routes.The experimental results show that the accuracy, coverage and prevalence of this method are higher than those of traditional methods, with the highest accuracy of 99.7%.

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Publication Details

Journal
International Journal of Reasoning-based Intelligent Systems
Published
2025-01-01
DOI
https://doi.org/10.1504/ijris.2025.145078
Primary Topic
E-commerce and Technology Innovations
Type
article
Field-Weighted Citation Impact
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article

Personalised recommendation of regional tourism routes based on weighted matrix factorisation

Guojing Fan, Lu Chen, Hui Cai, Fan Pan et al.
International Journal of Reasoning-based Intelligent Systems
E-commerce and Technology Innovations
article

Personalised recommendation of regional tourism routes based on weighted matrix factorisation

Guojing Fan, Lu Chen, Hui Cai, Fan Pan, Qiang Wu
article en

Abstract

In order to improve the recommendation accuracy and scenic spot coverage of tourism route recommendation methods, this paper proposes a new regional tourism routes personalised recommendation method based on weighted matrix factorisation.Firstly, according to the frequent tourism location sequence, the user tourism preference model is constructed to mine the user tourism preference.Secondly, from the two aspects of influence weight and time weight of tourist attractions, the weighted scoring matrix of tourist attractions is constructed.Finally, the weighted matrix is dimensionally reduced by using the matrix factorisation method, and the prediction scoring matrix is constructed to score the scenic spots in the scenic spots collection, and the top N scenic spots with higher scores are recommended to users as personalised tourist routes.The experimental results show that the accuracy, coverage and prevalence of this method are higher than those of traditional methods, with the highest accuracy of 99.7%.

International Journal of Reasoning-based Intelligent SystemsVol. 17(1)
Decent work and economic growth
Openalex Percentile: Top 92%
E-commerce and Technology Innovations
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Personalised recommendation of regional tourism routes based on weighted matrix factorisation — Guojing Fan, Lu Chen, et al. · International Journal of Reasoning-based Intelligent Systems (2025) | TGRS Research Map | TGRS