Application and Optimization Exploration of Quantum Computing in Real-Time Recommendation System for E-Commerce Platforms

Abstract

Quantum computing, with its excellent parallel computing capability and efficient data processing ability, has opened up new possibilities for real-time recommendation systems in the e-commerce field. With the increasing diversity of consumer demands and the rapid growth of data volume, traditional recommendation algorithms struggle to meet evolving requirements. Quantum technology can significantly improve the prediction speed of user preferences and facilitate real-time product recommendations. However, in the actual deployment process, there are still many challenges such as algorithm complexity, hardware environment limitations, privacy protection, and system compatibility. This article aims to explore in depth the typical application scenarios and optimization solutions of quantum computing technology in real-time e-commerce recommendation, with the aim of promoting the construction of a more intelligent and accurate user recommendation system.