Research on the Realization of Travel Recommendations for Different Users Through Deep Learning Under Global Information Management

This article is mainly to study the realization of travel recommendations for different users through deep learning under global information management. The personalized travel route recommendation is realized by establishing personalized travel dynamic interest (PTDR) algorithm and distributed lock...

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Bibliographic Details
Published in:Journal of global information management 2022-01, Vol.30 (7), p.1-16
Main Authors: Zhang, Xu, Song, Yuegang
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Customization
Deep learning
Information management
Knowledge management
Social networks
Tourist attractions
Tourists
User needs
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Summary:This article is mainly to study the realization of travel recommendations for different users through deep learning under global information management. The personalized travel route recommendation is realized by establishing personalized travel dynamic interest (PTDR) algorithm and distributed lock manager (DLM) model. It is hoped that this model can provide more complete data information of tourist destinations on the basis of the past, and can also meet the needs of users. The innovation of this article is to compare and analyze with a large number of baseline algorithms, highlighting the superiority of this model in personalized travel recommendation. In addition, the model incorporates the topic factor features, geographic factor features, and user preference features to make the data more in line with user needs and improve the efficiency and applicability of the model. It is hoped that the plan proposed in this article can help users make choices of tourist destinations more conveniently.
ISSN:1062-7375
1533-7995
DOI:10.4018/JGIM.296145