The design and implementation of personalized news recommendation system
Xuejiao Han, Wenqian Shang, Shuchao Feng · 2015
With the development of network information technology, a lot of news comes into the view of Internet users. We have entered the “information overload” era. So how to find useful information becomes more and more important. Personalized news recommendation is a kind of technology to find the news that users want to get urgently. It is based on the browsing history of many users. Through analysis of their interests, we can realize the personalized news recommendation for different people. In our system, we propose an improved association rules. This method associates with collaborative filtering algorithm to form a hybrid recommendation algorithm. Through using this new algorithm, we can generate recommendation lists and realize the personalized news recommendation.