Personalize News Recommendation System by Using Stack Auto Encoder

The popularity of Internet and mobile Internet, people are facing serious information overloading problems now a days. Recommendation engine is very useful to help people to reach the Internet news they want through the network. Recommender Systems have become the vital role in recent years and are utilized widely in various areas of social importance. In day to day life, users will not be able to read news every day due to heavy schedule. So to increase General knowledge of users we propose online recommendation systems which recommend news. In existing system i.e. news delivery portals deliver popular news on home page of the portal but user’s data according recommendation is not implemented yet. To overcome existing system problems we propose new recommendation system which automatically finds the news based on user’s profiles. Using the stack auto encoder algorithm.