Design And Implementation Of Scenic Spot Recommendation System Based On Scenic Spot Status Information

With the gradual intellectualization of various application scenarios of smart tourism,intelligent recommendation of tourist attraction has become one of the current research hotspots of smart tourism.The traditional scenic spot recommendation system urgently needs improvement,and a new intelligent recommendation system for scenic spots based on scenic spot status information is a good research idea.The system design takes into account the personal preferences of tourists,the degree of attraction congestion,geographical location,and movement direction and speed.It adopts big data optimization training,hoping to provide more convenient ways for tourists to obtain tourism information,increase diversified choices,and improve the tourism experience.The intelligent recommendation system designed in this article consists of two main parts.In the first part,Java language and Spring Boot framework are used for back-end development,and Java Script and Vue framework are used for front-end development.This system can achieve interaction between users and the system on the web,collect user preference information,and manage and display scenic area status information.User data and status information of scenic spots are stored in the My SQL database.In the second part,the main focus is on designing and implementing the scenic spot recommendation algorithm.The system adopts a Res Ne Xt50 convolutional neural network that introduces attention mechanism,taking scenic spot status information,tourist current location,and user preference information collected by the system as inputs.Based on the status information of users and scenic spots,intelligent recommendation of scenic spots is carried out for each user.Users can interact with the system through a mobile browser,and the system will recommend attractions that meet their needs based on their real-time location and preference information.