Improving Privacy and Recommendation Accuracy Advancements for Collaborative Filtering in Diverse Service Environments

This research improves recommendation systems by introducing new methods to better predict customer preferences and protect privacy. It proposes a technique that suggests a wider variety of products based on shopping patterns, helping users discover less common items. Another method increases the novelty of recommendations, ensuring customers find new and interesting products. Finally, a privacy-focused approach allows organizations to work together on improving recommendations without sharing sensitive data. These advancements aim to enhance customer satisfaction and safeguard privacy, benefiting both consumers and businesses in various sectors.