Research On POI Recommendation With Multiple Scenarios Based On Location-based Social Networks

Along with the rapid development of Web2.0 technology and GPS information coordination technology,Location-Based Social Networks was derived from traditional social networks,and the recommendation of Point-of-Interest(POI)as a core component of locationbased social networks has attracted widespread attention from researchers at home and abroad.Most current POI recommendation algorithms only calculate the similarity between users through common access terms(POI)between users.Due to the high sparseness of the data,the result of the POI recommendation is not accurate.In order to solve the above problem,this paper proposes a method of POI recommendation with multiple scenarios based on Location-Based Social Network.The social network is transformed into a friend set,and a user interest information model is established based on the user and POI look-up table method,which reduces the running time of POI recommendation and improves the recommendation efficiency.The LDA model is used to model the user's emotions,calculate the topic probability distribution of user reviews,and dig out the similarity of users in emotional tendencies.Analyze geographic impact information,establish geographic impact information models,and calculate geographic information access probability.Through the mining of the user's multiple context information,the problem of using multiple scenario information for POI recommendation in the research of Location-based social network is better solved.The experimental results show that the method of POI recommendation with multiple scenarios based on Location-Based Social Network proposed in this paper can improve the accuracy of recommendation,reduce the impact of data sparsity,and improve the efficiency of recommendation.Compared with other mainstream recommendation models,it has significantly improved the precison and recall evaluation indicators.