Design And Implementation Of Personalized Adaptation System For Radio And Television Industry Based On Online Recommendation

With the development of society,people spend more time on the Internet,and a lot of logs will be generated when using the Internet.At the same time,people will generate content on the Internet more frequently.In the Early time of the internet,information was mainly generated by major platforms,and the amount was small.People used information retrieval to obtain the information they wanted.As the development of the Internet,everyone is a participant in content producing.Face to the massive content,the recommendation system is the best solution.Content recommendations make users freed from frequent information retrieval actions recommended and better cater to the UGC(user generated content)environment of the Internet.At the same time,it can also analyze the accumulated large amount of logs to obtain valuable information,better serve users,and form a virtuous circle.Radio and Television Group has a large number of users,a large amount of user information and data,and also generates a large number of logs.In the past,the recommended content of Radio and Television Group was limited and monotonous.Now,a system that can analyze massive logs and user information is needed to personalize and adapt each user for content recommendation.The purpose is to quickly and accurately discover the user's interest preferences and recommend corresponding TV products.The Goal is the system understands the user more than the user itself.The system focuses on online recommendations to make real-time and efficient recommendations for different broadcast and television user scenarios.Because of the personal work content,the system will be detailed from an engineering perspective,mainly including the big data computing platform and high-performance data warehouse for data analysis,efficiently analyze user and content logs to form user and behavior portraits;use algorithm engineering abstraction,rely on the abstract algorithm library to realize automatic monitoring and operation of the algorithm;different scenarios use different strategies,and finally implement recommendations in various broadcasting and television user scenarios.