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.