Real-time Compliance Risk Identification and Decision-Making for Cross-border E-commerce Stores Using Multimodal NLP and Dynamic Knowledge Graph

DOI

10.2991/978-94-6239-598-5_31How to use a DOI?

Keywords

Cross-border E-commerce; Multimodal NLP; Dynamic Knowledge Graph; Compliance Risk; Real-time Decision-making

Abstract

With the booming development of global cross-border e-commerce, store operations face increasingly complex and dynamic compliance risks including platform regulations, laws and regulations, and intellectual property. Traditional audit methods struggle to achieve efficient and comprehensive risk management. To address this, this paper proposes a real-time compliance risk identification and decision-making model for cross-border e-commerce stores that integrates multimodal natural language processing (NLP) with dynamic knowledge graphs. The research first constructs a multimodal data fusion framework that comprehensively utilizes product text descriptions, user reviews, and product images to collaboratively extract potential risk features through multimodal NLP technology. Subsequently, a dynamic knowledge graph construction and real-time update mechanism is designed to link external regulations, platform policies, and internal analytical entities, forming an evolving and reasoning knowledge network. Building on this foundation, the paper establishes an integrated “perception-cognition-decision” theoretical model. Through multimodal NLP for risk perception and dynamic knowledge graphs for deep association and reasoning cognition, the system ultimately provides automated decision-making recommendations for risk disposal. This study offers an innovative theoretical framework and methodological support for intelligent supervision of compliance risks in cross-border e-commerce, demonstrating significant theoretical value and practical application potential for enhancing corporate compliance efficiency and reducing operational risks.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Jiang Lu
AU  - Chuxuan Lu
AU  - Ling Lu
PY  - 2026
DA  - 2026/02/26
TI  - Real-time Compliance Risk Identification and Decision-Making for Cross-border E-commerce Stores Using Multimodal NLP and Dynamic Knowledge Graph
BT  - Proceedings of the 2025 6th  International Conference on Big Data and Social Sciences (ICBDSS 2025)
PB  - Atlantis Press
SP  - 317
EP  - 323
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6239-598-5_31
DO  - 10.2991/978-94-6239-598-5_31
ID  - Lu2026
ER  -