  The number of Internet users had grown rapidly enticing companies and
cooperations to make full use of recommendation infrastructures. Consequently,
online advertisement companies emerged to aid us in the presence of numerous
items and users. Even as a user, you may find yourself drowned in a set of
items that you think you might need, but you are not sure if you should try
them. Those items could be online services, products, places or even a person
for a friendship. Therefore, we need recommender systems that pave the way and
help us making good decisions. This paper provides a review on traditional
recommendation systems, recommendation system evaluations and metrics,
context-aware recommendation systems, and social-based recommendation systems.
While it is hard to include all the information in a brief review paper, we try
to have an introductory review over the essentials of recommendation systems.
More detailed information on each chapter will be found in the corresponding
references. For the purpose of explaining the concept in a different way, we
provided slides available on
https://www.slideshare.net/MahdiSeyednejad/recommender-systems-97094937.
