Research And Design Of Location Recommendation Algorithms Of Interest To Users Based On Real-time Location

In recent years,with the rapid development of the Internet,the amount of network information is increasing explosively.Although the vast amount of information allows users to have more choices,it also causes confusion and helplessness when users choose information.Therefore,relevant scholars have begun to study various methods to solve this problem,and the recommendation system is a solution that is more effective for this problem.The basic idea of the recommendation algorithm is to mine and analyze the user's historical behavior data,deeply understand the relationship between the user and the project,and help the user to select the content that the user is most likely to be interested to recommend to the user in the vast amount of information,so that the user no longer feeling helpless when they facing vast amount of information,and the solution of the recommendation system has alleviated this problem to some extent,providing a relatively convenient personalized recommendation service for the majority of Internet users^[1].At the same time,with the rapid development of mobile communication devices,its convenience and portability make users prefer to obtain information through mobile devices in daily life,so the application of recommendation technology to mobile intelligent devices is also the trend of the times^[2].When the recommendation system on the mobile device recommends information for the user,we need to consider more influential factors in the real-time location.Users will have different actual needs depending on their actual geographical location.In order to better study the use of mobile intelligent devices to generate satisfactory results for users,this paper analyzes the current development status of existing personalized recommendation technologies and compares various recommendation algorithms by studying the relevant content of recommendation technologies.A location recommendation algorithm that uses the user's actual geographic location as a starting point and the user's interest preference to generate more accurate and higher quality for the user is proposed.The main work of this paper is as follows:?1?This paper proposes a location-based personalized recommendation algorithm,which considers the three influencing factors by calculating the impact of location sign-in similarity,location tag similarity and distance between locations.To generate preliminary location recommendations for users.?2?This paper designs a method for calculating user score characteristics,which predicts the user's preference for certain labels by analyzing the user's rating data of the location,and predicts the user's preference for a new location through comprehensive evaluation.?3?Based on the above related research content,this paper proposes a location recommendation algorithms of interest to users based on real-time location.This algorithm takes into account the user's interest and the location uncertainty when the user uses the mobile device,which generates more high quality location recommendations for mobile device users.?4?This paper designs an APP application system based on Android platform.Location recommendation algorithms of interest to users based on real-time location proposed in this paper is applied to the system,and the main core functions of the system are realized.The algorithms proposed in this paper is verified by the system designed by this paper.