Model Analysis of Collaborative-Based Recommender System

With the data growing in abundance amount and usage of social media increasing day by day, the features of Youtube videos, video streaming apps, e-commerce sites etc. have been an important concern for the companies. Every user wants the recommendation according to his or her choice. Therefore, it becomes very important for these applications and sites to have an efficient recommender system that not only recommends the result as per the user but also do not overlay excessive burden on the applications. In this paper, we would be analyzing the collaborative-based recommender system algorithms like (Pearson, cosine and matrix factorization) that are used under the different models of collaborative-based recommender systems. Following on the basis of which, we have proposed a generic book recommender system that works under the collaborative-based architecture.