  Nowadays, it's a very significant way for researchers and other individuals
to achieve their interests because it provides short solutions to satisfy their
demands. Because there are so many pieces of information on the internet, news
recommendation systems allow us to filter content and deliver it to the user in
proportion to his desires and interests. RSs have three techniques:
content-based filtering, collaborative filtering, and hybrid filtering. We will
use the MIND dataset with our system, which was collected in 2019, the big
challenge in this dataset because there is a lot of ambiguity and complex text
processing. In this paper, will present our proposed recommendation system. The
core of our system we have used the GloVe algorithm for word embeddings and
representation. Besides, the Multi-head Attention Layer calculates the
attention of words, to generate a list of recommended news. Finally, we achieve
good results more than some other related works in AUC 71.211, MRR 35.72,
nDCG@5 38.05, and nDCG@10 44.45.
