ABSTRACT
In recent years, recommendation systems which help to suggest several items such as movie, friends, books to users have become more and more famous. These systems gather and analyze data from user’s behavior, activities or preferences. After that it predicts what users will like depending on similarity among users. Now-a-days, friend recommendations have become most popular with the development in social networking systems. The existing system recommends a friend based on mutual friends. This does not reveal users’ choices about their friend selection in real life. Recommending friends based on the user life styles prove to be more realistic. In this paper various friend recommendation techniques are surveyed and comparison among them is done. Also several models are studied and analyzed to form the base of this paper.
