Published Paper Details:

With the constant proliferation of web applications around the world, it is difficult to obtain the appropriate information needed by the user in a short period of time.The number of handheld mobile devices is growing, and the majority of business revolves around data search. It is quite difficult to obtain essential information from online apps without a robust recommender system. Recommender systems are used in web applications to give relevant data to users depending on their preferences and interests. Different types of recommender systems have been presented to meet various needs. Collaborative filtering recommender systems and content based recommender systems are the two most fundamental forms of recommender systems. These two recommender systems are sometimes combined to improve the efficiency of a recommender system. The new recommender system that was created is known as a hybrid recommender system. This paper's goal is to assist readers grasp the fundamentals of recommender systems. This report lists significant research fields that are open to new researchers. After reading this work, new researchers will have a better understanding of the fundamental challenges with recommender systems that need to be addressed.