A hybrid news recommendation algorithm based on user's browsing path

In the process of the rise of Internet, journalism industry has been impact greatly as a traditional media. And as a very important Internet technique to meet the needs of users, personalized recommendation has been paid much more attention currently by a great number of researchers who were engaged in the journalism industry. Personalized recommendation algorithm has been extensively studied, and a lot of algorithms have been proposed. Those algorithms can meet user's need to a certain extent, but there also exist some problems. In this paper, our research mainly focuses on the user's browsing path, then design a personalized news recommendation algorithm to analysis and simulate user's habits, then on this basis to predict user' s behavior and evalue user's fitness.