Research And Implementation Of News Recommendation System For Mobile Terminals

With the rapid development of internet technology, we are in the age of Big Data. We are facing more and more digital information in our daily life and work. Facing the problem of information overload, to make users access to the information they need more quickly and effectively is becoming the focus of research among scholars. Recommendation system recommend personalized information for different users by a variety of recommendation algorithm. It somehow solve the problem that users can’t find the information they need effectively. In recent years, the mobile internet is also facing the problem of information overload with the popularity of mobile devices. As the mobile devices have smaller screens compared with traditional internet, it needs to use the screen more efficiently and rationally.It has been more than twenty years since the recommendation algorithm was brought up. Collaborative filtering recommendation algorithm was been prefered because it is unrelated to the content of the items to be recommended. With the widely used of the recommendation system in recent years, the hybrid model recommendation algorithm is being used in all kinds of systems. Researchers design different hybrid recommendation model depending on the system environment to get a better recommendation results.In this paper, we proposed a hybrid model of collaborative filtering recommendation algorithm added with time factor and geographic information based on the characteristics of the mobile terminal. This paper describes the current status of the recommendation algorithm and its development process. We study the principles of user similarity algorithm and do offline experiments based on data sets of collaborative filtering recommendation algorithm. And we focus on three collaborative filtering recommendation algorithms for their principles and recommend effectiveness. Adding the time factor and geographic information to the basic collaborative filtering recommendation algorithm for mobile terminals. Finally, we design and implement news recommendation system for mobile terminals. This system can recommend the news that user preferred based on their interests, and it improve the user’s reading efficiency and the user experience.