Combination of machine learning methods to solve cold start problem in recommender system
Nitin Kumar Mishra, Vimal Mishra, Saumya Chaturvedi · International Journal of Advanced Intelligence Paradigms · 2024
Recommender systems are a special type of intelligent systems which exploits historical of user rating on items to make the recommendation of items for those users. They are used in a wide range of applications like online shopping, e-commerce services social networking applications and many more. In our paper, we are solving a problem known as the cold start problem where the new user has a problem as he has the missing history. We have validated our solution on MovieLens dataset and found it to be solving cold start problem in a magical way. we claim our approach to be a novel approach for solving cold start problem using a combination of several methods some of which belong to collaborative filtering domain and others belong to content-based domain. We have done exhaustive testing to ensure no fault in the proposed method. The results shown by our method are promising.