Our Research “Personalized Recommendation Systems for E-Commerce on Social
Media Platforms using Big Data Analytics “is a as e-commerce offers more and more
choices for users, its structure becomes more and more complicated. Inevitably, it brings
about the problem of information overload. The solution to this problem is an e-commerce
personalized recommendation system using machine learning technology. People often
seem confused when facing extensive information and cannot grasp the key points. This
paper studies the personalized recommendation technology of e-commerce: deeply
analyzes the related technologies and algorithms of the e-commerce recommendation
system and proposes the latest architecture of the e-commerce recommendation system
according to the current development status of the e-commerce recommendation system.
The system recommends accuracy and real-time requirements and divides the system
into two parts: offline mining and online recommendation and analyzes and implements
the functions and technologies of each part. User-based recommender systems,
collaborative filtering recommender systems, and content-based recommender systems
are analyzed, respectively. The personalized recommendation cannot only quickly...