Design And Implementation Of A Personalized News Recommendation System Based On Collaborative Filtering

It is difficult for users to retrieve their interested content accurately and efficiently with the rapid growth of network information.Therefore,personalized recommendation technology emerges as the times require,which solves this problem effectively.Based on personalized recommendation technology,personalized news recommendation system is a system pushing news that may be interesting to users according to their previous reading habits.By bringing personalized service experience to users,personalized news recommendation system can enhance the viscosity of users effectively and avoid the loss of users.The main research contents of this paper include putting forward personalized news recommendation model,improving traditional collaborative filtering algorithm and implementing personalized news recommendation system with mobile platform.The personalized news recommendation model consists of four modules:news classification,user interest analysis,user clustering and the generation of recommendation results.Improved algorithm initially applies average value of users’ evaluation and degrees of population of items to fill in the default value,then combined with the time attenuation function,the user rating data is set the corresponding time weight.The requirements of the personalized news recommendation system based on android platform are analyzed firstly,and then the design of the system is introduced detailed,finally,by integrating the improved recommendation algorithm into the system effectively,the development of android-based personalized news recommendation system has been accomplished.In this paper,a personalized news recommendation model is proposed,and the traditional collaborative filtering algorithm is improved.Finally,a personalized news recommendation system based on android platform is designed and implemented.The personalized news recommendation system based on android platform accords with the era background of mobile Internet,and has certain research value and application significance by bringing the personalized customization service experience to users.