Please use this identifier to cite or link to this item: https://dspace.ctu.edu.vn/jspui/handle/123456789/94020
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dc.contributor.advisorNguyễn, Thái Nghe-
dc.contributor.authorNguyễn, Duy Khang-
dc.date.accessioned2023-12-28T03:06:57Z-
dc.date.available2023-12-28T03:06:57Z-
dc.date.issued2023-
dc.identifier.otherB1910654-
dc.identifier.urihttps://dspace.ctu.edu.vn/jspui/handle/123456789/94020-
dc.description69 Trvi_VN
dc.description.abstractCurrently, suggestion systems are being widely applied in most fields (such as e-commerce, entertainment, education, tourism,...) to help users easily make their choices thanks to personal information or feedback (rating). The thesis focuses on researching a collaborative filtering recommendation system based on Keras's RecommenderNet model to predict the user's suitability for a tourist destination based on the user's rating history, and then suggest a list destination place to the user, and content-based recommended by vectorizing TF-IDF to convert feature place data into TF-IDF matrix and then use to calculate the cosine similarity between the vectors after that provide a list of a suggested destination place for the user. Finally, I apply this research to build a "tourist destination recommendation system" for users by combining collaborative filtering and content-based filtering, suggesting destinations for tourists, and integrating Vietmap to provide easy directions to tourist destinations.vi_VN
dc.language.isoenvi_VN
dc.publisherTrường Đại Học Cần Thơvi_VN
dc.subjectCÔNG NGHỆ THÔNG TIN - CHẤT LƯỢNG CAOvi_VN
dc.titleTOURIST DESTINATION RECOMMENDATION SYSTEMvi_VN
dc.title.alternativeHỆ THỐNG GỢI Ý ĐỊA ĐIỂM DU LỊCHvi_VN
dc.typeThesisvi_VN
Appears in Collections:Trường Công nghệ Thông tin & Truyền thông

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