Design And Implemention Of Poi Personalized Recommendation System Based On Heterogeneous Social Network

With the continuous development of positioning technology,personalized recommendation of POI(point of interest)has become one of the hot research points in the recommendation field.At present,POI recommendation research has many disadvantages such as diversity of demand,huge amount of data,sparse data,and low recommendation accuracy.In this paper,through the rigorous algorithm calculation and experimental comparison,a better design scheme is obtained.The following are the main researches of this article:(1)In-depth study of the POI theoretical and technical basis,combining heterogeneous information networks with location-based social networks,to a certain extent,improved the sparse user data problems,and mined user POI preferences.(2)This paper puts forward the idea of combining theoretical analysis and system verification,explores the theory of combining heterogeneous information networks and personalized POI recommendations,designs and implements POI personalized recommendation systems based on heterogeneous social networks and logistic regression algorithms,and provides innovative ideas for POI personalized recommendation research.(3)This paper constructs a heterogeneous social network model and focuses on research and design of POI recommendations based on heterogeneous social networks.Finally,the POI recommendation system was designed to implement the database,Web services,and system processing modules.Solved the user's personalized needs,improved the accuracy of the POI personalized recommendation system.(4)The open data set was used for rigorous experimental comparison and verification,and it was concluded that the recommendation algorithm of this paper has a better improvement in accuracy and recall rate.And multi-dimensional test cases are used to test and verify the system,It is concluded that the recommendation system of this paper has certain superiority and advancement.The POI recommendation is a location-based social networking service that benefits users and businesses.In recent years,some POI recommendation algorithms have been proposed,but there is still a lack of system design and implementation.This paper proposes a POI recommendation algorithm based on meta-path selection and designs a POI recommendation system,which verifies the feasibility of the algorithm and the stability of the system.The study of POI personalized recommendation technology will greatly increase the efficiency of the application and development of POI recommendation.It will not only enhance the user's stickiness in POI recommendation service,but also promote and promote POI and generate substantial business value,thus providing user and POI recommendation services.Providers and merchants around POI bring greater benefits,so the research of POI personalized recommendation has great social and economic significance.