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Advanced Hybrid Information Processing. 7th EAI International Conference, ADHIP 2023, Harbin, China, September 22-24, 2023, Proceedings, Part III

Research Article

Personalized Recommendation Method of Rural Tourism Routes Based on Mobile Social Network

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  • @INPROCEEDINGS{10.1007/978-3-031-50549-2_10,
        author={Yi Liu and Qingqing Geng},
        title={Personalized Recommendation Method of Rural Tourism Routes Based on Mobile Social Network},
        proceedings={Advanced Hybrid Information Processing. 7th EAI International Conference, ADHIP 2023, Harbin, China, September 22-24, 2023, Proceedings, Part III},
        proceedings_a={ADHIP PART 3},
        year={2024},
        month={3},
        keywords={Mobile Social Network Rural Tourism Routes Personalized Recommendation Message Hops Geographical Factor Characteristics Vectorization Data Denoising Route Sequence},
        doi={10.1007/978-3-031-50549-2_10}
    }
    
  • Yi Liu
    Qingqing Geng
    Year: 2024
    Personalized Recommendation Method of Rural Tourism Routes Based on Mobile Social Network
    ADHIP PART 3
    Springer
    DOI: 10.1007/978-3-031-50549-2_10
Yi Liu1, Qingqing Geng1,*
  • 1: Chongqing College of Architectural and Technology
*Contact email: gqq123cq@163.com

Abstract

The existing personalized recommendation methods for tourism routes have the problem of low tourist satisfaction, so a personalized recommendation method for rural tourism routes based on mobile social networks is proposed. According to the mobile social network model, calculate the number of mobile message hops and define a set of social information paths to complete the processing of travel route data based on mobile social networks. On this basis, implement denoising of tourism route data, determine personalized route recommendation schemes by deriving route sequences, and complete the design of personalized rural tourism route recommendation methods based on mobile social networks. The experimental results show that under the influence of the above methods, the number of tourists choosing fixed tourism routes significantly increases, and the satisfaction level of tourists with the recommended routes also increases, which meets the practical application needs of personalized recommendation of rural tourism routes.

Keywords
Mobile Social Network Rural Tourism Routes Personalized Recommendation Message Hops Geographical Factor Characteristics Vectorization Data Denoising Route Sequence
Published
2024-03-24
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-50549-2_10
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