The Design And Implementation Of Tourism Route Recommendation System In Rizhao City

With the target of building a well-off society in an all-round way being accomplished,people's living conditions have improved steadily and there are more and more people choosing to travel on holidays.However,most of the tourist routes provided by travel agencies or travel websites are set in advance and users can't individually plan their tourist routes according to their needs and interest towards tourist sites.So these tourist routes can't meet personalized needs of users.Therefore,how to enable users to plan appropriate tourist routes that will satisfy their own needs before they set off is the key problem we need to solve in this paper.Firstly,the article adopts the idea of combining the recommendation systems and route planning to propose a calculation method which is based on the multi-attribute route recommendation value.Then,we combine the calculation method with route planning algorithm so that it can help users to plan tourist routes.Secondly,the proposed method is applied to the tourist route recommendation system of Rizhao City.The system can not only recommend appropriate tourist sites to users,but also enable users to plan their tourist routes according to their interests and the attributes of tourist sites.In this way,the system can help users simplify their preparation and satisfy personalized needs of different users.Specifically,the research work in this paper are as below:(1)Firstly,we obtain the predicted value of users towards tourist sites through combing itembased CF(Collaborative Filtering)with temporal function which is based on human's forgetting pattern.Then we combine the values with three other factors including suitable time of visiting a site,the level of a tourist site and the ticket price of a tourist site to get multi-attribute route recommendation value.Secondly,according to the weaknesses of the ant colony optimization in terms of tourist routes planning,we have enhanced the existing ant colony optimization to adopt Multi attribute ant colony optimization(MAACO).In the proposed algorithm,the multi-attribute route recommendation value is added to the path selection probability of the original ant colony optimization,which enables ant colony optimization to consider the factor of personalized needs of different users and the attributes of tourist sites in aspect of route planning.In addition,we set a reasonable range of pheromone values.Therefore,the most appropriate tourist route will be recommended to user and the user's satisfactory will be improved.The experimental results show that the proposed algorithm has better performance than ant colony optimization.(2)According to above mentioned research content and the analysis of practical needs,we design and implement the tourist route recommendation system of Rizhao City.The front-end modules of the system utilizes the Vue framework and Element to implement six modules including module of login registration,model of tourist sites recommendation,module of route recommendation,module of gourmet food,module of personal information and module of attractions comments.In the module of route recommendation,we use the MAACO algorithm to perform tourist route recommendation and display the recommended routes on webpage based on the Baidu Map API,so that users can view the recommended routes and the related content of tourist sites on the map.The back-end modules of the system include module of tourist sites management,module of food management,module of user management and module of comment management,which utilize SSM(Spring+Spring MVC+Mybatis)framework to implement.Finally,large amounts of tests are conducted on the systems and show that the system can help users to make reasonable travel route recommendation.Other modules of the system have reached the design goals and the system can operate normally.