Research Of Performance Monitoring And User Behavior Analysis On IOS Application

In recent years,with the rapid spread of smart phones and mobile Internet,mobile applications also showed explosive growth.As a carrier to provide users with a variety of needs,the role of mobile applications in people's daily lives becomes more and more important.However,at the same time,a variety of problems have been exposed,such as the quality of applications is vary widely,the contents of applications are similarity,malicious applications are continuing to emerge and so on.Therefore,as a developer,it's urgent to enhance the quality of applications and improve the user experience.Monitoring the performance and analysing the user behaviors of applications is one of the ways to solve these problems.First of all,this paper makes a research on related technologies about mobile applications performance monitoring and user behavior analysis which is based on custom event in domestic and abroad,and then,a platform about performance monitoring and user behavior analysis based on iOS mobile applications is designed and implemented.The platform is composed of the following three modules:(1)A performance monitoring SDK about data access for iOS applications.Through non-intrusive code injection,the module can make the real-time monitoring of HTTP requests,data persistence operations and the loading performance of UIWebView realize with a simple configuration.(2)Build user portraits and groud portraits based on custom events.The developers import the SDK,and installing the monitoring point in the process which need to be monitored.And then,analysing and constructing user portraits and community portraits through the service,and displaying the result on the Web side.After that,mining the user habits,then help developers to adjust the layout of the controls or the organizational structure among pages.(3)An improved fuzzy C-means(FCM)clustering algorithm is designed,and then analyze the behavior informations to divide the users into different clusters,and the situation of users' access in various of clusters will be analysed and visualized in order to provide decision-making basis for later product marketing and personalized recommendation.Finally,this paper analysed a typical E-commerce mobile application to demonstrate the overall process of using the platform in detail and verify the effectiveness of the performance monitoring scheme data access and user clustering analysis algorithm through experiments.