With the information explosion of news articles, personalized news recommendation has
become important for users to quickly find news that they are interested in. Existing methods
on news recommendation mainly include collaborative filtering methods which rely on direct
user-item interactions and content based methods which characterize the content of user
reading history. Although these methods have achieved good performances, they still suffer
from data sparse problem, since most of them fail to extensively exploit high-order structure …