Personalized Travel Route Recommendation Model of Intelligent Service Robot Using Deep Learning in Big Data Environment
Aiming at the problems that the traditional model is difficult to extract information features, difficult to learn deep knowledge, and cannot automatically and effectively obtain features, which leads to the problem of low recommendation accuracy, this paper proposes a personalized tourism route rec...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Journal of Robotics |
| Online Access: | http://dx.doi.org/10.1155/2022/7778592 |
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| _version_ | 1832563667340623872 |
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| author | Xiang Huang |
| author_facet | Xiang Huang |
| author_sort | Xiang Huang |
| collection | DOAJ |
| description | Aiming at the problems that the traditional model is difficult to extract information features, difficult to learn deep knowledge, and cannot automatically and effectively obtain features, which leads to the problem of low recommendation accuracy, this paper proposes a personalized tourism route recommendation model of intelligent service robot using deep learning in a big data environment. Firstly, by crawling the relevant website data, obtain the basic information data and comment the text data of tourism service items, as well as the basic information data, and comment the text data of users and preprocess them, such as data cleaning. Then, a neural network model based on the self-attention mechanism is proposed, in which the data features are obtained by the Gaussian kernel function and node2vec model, and the self-attention mechanism is used to capture the long-term and short-term preferences of users. Finally, the processed data is input into the trained recommendation model to generate a personalized tourism route recommendation scheme. The experimental analysis of the proposed model based on Pytorch deep learning framework shows that its Pre@10, Rec@10 values are 88% and 83%, respectively, and the mean square error is 1.537, which are better than other comparison models and closer to the real tourist route of the tourists. |
| format | Article |
| id | doaj-art-dfd4fcd8771b41658c67bb8be3d9aefe |
| institution | Kabale University |
| issn | 1687-9619 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Robotics |
| spelling | doaj-art-dfd4fcd8771b41658c67bb8be3d9aefe2025-02-03T01:12:53ZengWileyJournal of Robotics1687-96192022-01-01202210.1155/2022/7778592Personalized Travel Route Recommendation Model of Intelligent Service Robot Using Deep Learning in Big Data EnvironmentXiang Huang0Hunan Mass Media Vocational and Technical CollegeAiming at the problems that the traditional model is difficult to extract information features, difficult to learn deep knowledge, and cannot automatically and effectively obtain features, which leads to the problem of low recommendation accuracy, this paper proposes a personalized tourism route recommendation model of intelligent service robot using deep learning in a big data environment. Firstly, by crawling the relevant website data, obtain the basic information data and comment the text data of tourism service items, as well as the basic information data, and comment the text data of users and preprocess them, such as data cleaning. Then, a neural network model based on the self-attention mechanism is proposed, in which the data features are obtained by the Gaussian kernel function and node2vec model, and the self-attention mechanism is used to capture the long-term and short-term preferences of users. Finally, the processed data is input into the trained recommendation model to generate a personalized tourism route recommendation scheme. The experimental analysis of the proposed model based on Pytorch deep learning framework shows that its Pre@10, Rec@10 values are 88% and 83%, respectively, and the mean square error is 1.537, which are better than other comparison models and closer to the real tourist route of the tourists.http://dx.doi.org/10.1155/2022/7778592 |
| spellingShingle | Xiang Huang Personalized Travel Route Recommendation Model of Intelligent Service Robot Using Deep Learning in Big Data Environment Journal of Robotics |
| title | Personalized Travel Route Recommendation Model of Intelligent Service Robot Using Deep Learning in Big Data Environment |
| title_full | Personalized Travel Route Recommendation Model of Intelligent Service Robot Using Deep Learning in Big Data Environment |
| title_fullStr | Personalized Travel Route Recommendation Model of Intelligent Service Robot Using Deep Learning in Big Data Environment |
| title_full_unstemmed | Personalized Travel Route Recommendation Model of Intelligent Service Robot Using Deep Learning in Big Data Environment |
| title_short | Personalized Travel Route Recommendation Model of Intelligent Service Robot Using Deep Learning in Big Data Environment |
| title_sort | personalized travel route recommendation model of intelligent service robot using deep learning in big data environment |
| url | http://dx.doi.org/10.1155/2022/7778592 |
| work_keys_str_mv | AT xianghuang personalizedtravelrouterecommendationmodelofintelligentservicerobotusingdeeplearninginbigdataenvironment |