Recommendation Systems: Techniques, Challenges, Application, and Evaluation

With this tremendous growth of the Internet, mobile devices, and e-business, information load is increasing day by day. That leads to the development of the system, which can filter and prioritize the relevant information for users. Recommendation system solves this issue by enabling users to get knowledge, products, and services of personalized basis. Since the inception of recommender system, researcher has paid much attention and developed various filtering techniques to make these systems effective and efficient in terms of users and system experience. This paper presents a preliminary survey of different recommendation system based on filtering techniques, challenges applications, and evaluation metrics. The motive of work is to introduce researchers and practitioner with the different characteristics and possible filtering techniques of recommendation systems.

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