User Behavior Analysis Of Internet TV Platform Based On User Portrait Technology

In recent years,with the rapid development of Internet technology,intelligent TV has gradually replaced traditional TV,and Internet TV has become a new home entertainment terminal.The service content and information of Internet TV platform are becoming more and more abundant,but the problem of information overload exists when individual users watch TV programs.At present,the trend of big data has been hard to reverse.How to use this technology to continuously mine the user's preferences,find the special rules of user's behavior habits,and personalized launch the corresponding content services based on the understanding of user's behavior preferences,so as to improve the effective play volume of platform content.In view of this,based on the user portrait technology,this paper proposes a user behavior model.In the actual case study,using the original user data of high-definition film and television application to verify the effectiveness and feasibility of the method,the main work of this paper is as follows:(1)based on the user profile technology and the basic principle of collaborative filtering algorithm,the user behavior model is established.(2)collect 40 users' original behavior data of Internet TV HD film and television application,and verify the user behavior model.(3)the implementation of the model and method proposed in this paper in the EPG content publishing and management system adds the intelligent recommendation part of the system and the display interface of the background and front-end,and verifies the feasibility and effectiveness of the method proposed in this paper with data analysis and feedback.