Comparative analysis of recommendation system

During the last two decades we have witnessed the tremendous amount of growth in e-commerce industry. People all over the world buy articles just by a click of mouse. Today recommendation system is an important part of almost every website. A user might not be able to find out all the desired articles and items from the endless information pool available on the internet. Recommender system suggests those items to the user which are most suitable to the user based on his data of items purchased and his ratings collected over a period of time, which helps to predict the buying behavior of the user. In this paper we will present an overall explanation of the recommendation system and compare the features of different types of recommendation systems and try to figure out that which type of recommendation technique gives optimum results in library and information services.