Research on Tourism Route Recommendation Strategy Based on Convolutional Neural Network and Collaborative Filtering Algorithm

With improving people’s living standards, tourism has become essential leisure and entertainment. At present, it begun to shift from a quantity-oriented method quality-oriented method. It is difficult for passengers choose the route that suits them numerous routes. Given above problems, this study proposes travel recommendation algorithm combines convolutional neural network collaborative filtering. The uses extract latent features in customer itinerary data then matrix factorization based on filtering perform score prediction. experimental results show can meet requirements of different customers. same time, accuracy tourist improved, technology are provided realizing personalized service route.