Research On Rural Tourism Wechat Application Platform Based On Rough Set Intelligent Recommendation

The Internet has entered a new era for Internet of Everything with the rapid development of network technology.Everything become data in digitalized network.The big data resources facilitate people's life and meanwhile cause confusions.It is not easy for people to find the correct information from the massive database which is increasing day by day..The main purpose of intelligent recommendation system is to help people find the correct information quickly.By combining some relevant features of the reached information,the Intelligent Recommendation System finally recommends the foremost information to users by analyzing users' interests and preferences.It is very important to improve the accuracy of recommendation result since traditional intelligent recommendation usually with very low accuracy for it focuses on the similarity between product and user information,and pay less attention to other information like the current behavior of users and location etc.Aiming at solving the problem of low accuracy in recommend results of the current recommendation system,this paper establishes an intelligent recommendation model for rural tourism based on rough set theory and ontology technology.This new model is validated via the Wechat program for rural tourism.The main research subjects of this paper is as below:(1)Summarize the common methods and puts forward the writer's view based on the writer's literature research on intelligent recommendation of tourism products;(2)Constructing the ontology model of rural tourism products and users through literature analysis and field survey of rural tourism products;(3)Through the basic theory of rough set and the common algorithm of attribute reduction,this paper studies the literature,and determines that the attribute reduction method based on difference matrix is used to reduce the attribute of rural tourism product information,and the kernel attribute is obtained.At the same time,combined with the user personalized dynamic interest model,the interest degree of the user to the product attribute is calculated,and then the recommendation of the rural tourism product is realized by the comprehensive calculation and ranking of the user interest and the similarity of the rural tourism product.(4)Designing a rural tourism Wechat program to validate the recommendation model.The results show that it is effective to use the user personalized intelligent recommendation model based on rough set theory to recommend product information to the users of WeChat platform for rural tourism.,which greatly improves the accuracy of user information recommendation.