The Application of Personalized Recommendation System Driven by Artificial Intelligence on E-commerce Platforms

With the rise and development of Internet technology, advanced technologies, including cloud computing and big data, have greatly enriched data processing and information access. However, the field of e-commerce faces the serious challenge of "information overload". To solve this problem, this study designs and implements a personalised recommendation system based on artificial intelligence technology. The system integrates data mining and machine learning algorithms, accurately analyses users' purchase records, browsing history and preference characteristics, and intelligently predicts and recommends products that users may be interested in through complex algorithmic models. Experimental results show that the system is significantly better than the traditional recommendation system in terms of recommendation accuracy and recall rate, reaching 0.912 and 0.923 respectively, effectively improving the user experience. This result not only provides a new idea for e-commerce personalised recommendation, but also opens up a new path for the application of AI technology in the field of information filtering and recommendation.