Design and Optimization of Intelligent Recommendation System Using Machine Learning

Intelligent recommendation system is a service that is widely studied in the field of data science, implemented through machine learning technology. This article proposes a design scheme for an intelligent recommendation system based on collaborative filtering, providing users with personalized and accurate recommendations. Label classification is crucial in intelligent recommendation, but there are still issues such as diversity, ambiguity, and spam labels. This article first introduces the traditional intelligent recommendation system and improves it a machine learning based intelligent recommendation system design scheme was proposed, and the effectiveness of the improved intelligent recommendation system was verified through experiments. The experimental results show that the intelligent recommendation system design proposed in this article can effectively solve some of the problems existing in traditional intelligent recommendation systems.