AI Intelligent Retrieval Application Practice in Cross-border E-commerce Information Management

Zheng Hao

University of Technology Sydney

Abstract：

With the continuous improvement of the digital trade system, cross-border e-commerce information management is characterized by multi-source and heterogeneity. Relying on natural language processing, multimodal recognition and knowledge graph technology, AI intelligent retrieval adapts to the information needs of multilingualism, cross-regional and dynamic updates in cross-border scenarios. This paper sorts out the practical paths of large model retrieval enhancement, image search product selection, dynamic knowledge graph and lightweight system integration around scenarios such as commodity matching, policy tracking, public opinion mining and supply chain scheduling, and presents the technology implementation forms with industry cases. AI intelligent retrieval promotes the transformation of cross-border e-commerce information processing from passive query to active perception, optimizes operational efficiency and decision-making accuracy, and provides technical support for the digital upgrading of the industry.

Key Words：

cross-border e-commerce; information management; AI intelligent retrieval; multimodal matching; knowledge graph