Recommender system: An analytical report on decision making for large scale online social networks

Abstract

Social networking playing a very important role in communication, business, and sharing of information. During these activities, a huge amount of data it generates. Organizations need to analyze, process, and then find patterns to take the decision. A recommender system can analyze Online Social Network (OSN) and recommends that leads to help the organization to take the decision. Ever growing Size of OSNs required a more efficient recommender system that provides more accurate results. The study reviews the different design issues of the recommender system and compares them with the real data set. This study analyses the different recommender systems and compares them to identify challenges and future scope for the design of the recommender system.