Large-scale recommender systems using Hadoop and collaborative filtering: a comparative study
With the rapid advancements in internet technologies over the past two decades, the amount of information available online has exponentially increased. This data explosion has led to the development of recommender systems, designed to understand individual preferences and provide personalized recommendations for desirable new content. These systems act as helpful guides, assisting users in discovering relevant and appealing information tailored to their specific tastes and interests. This study's primary objective is to assess and contrast the latest methods utilized