Personalized Product Customization Service Based on Fine-Grained and Precise Perception of Supply and Demand

Download PDF
Open Webpage

Kai Zhang, Yuchen Li, Bohai Zhao, Yongchao Xing, Hongliang Sun, Zhiying Tu, Dianhui Chu

Published: 2025, Last Modified: 05 May 2026ICWS 2025EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: In the era of industrial internet, achieving a dynamic balance between mass production and personalized customization has become a core demand for industrial development. This necessitates that product service systems can accurately capture users' personalized requirements. Although large language models (LLMs) possess powerful dialogue and reasoning capabilities, enabling them to identify implicit requirements, they still exhibit limitations in supply-demand matching, particularly in the precise alignment between personalized requirements and product capabilities. To this end, this study innovatively proposes a personalized product customization service framework (Req2Sol) based on fine-grained supply-demand cognition. This framework formalizes the modeling of supply-demand capabilities and finegrained personalized requirements through a knowledge graph (KG), integrating them into the LLM training process. This significantly enhances the model's understanding of supplydemand relationships, enabling accurate product configuration and customization recommendations. Firstly, a multi-view modeling approach for supply-demand capabilities and personalized fine-grained requirements is proposed, constructing a requirementproduct knowledge graph. Secondly, the knowledge graph is utilized as pre-training data to achieve domain-specific finetuning of LLMs. By introducing conditional scenarios and strategies, a five-level quantitative evaluation system for Req2Sol is established, improving its performance by 7.3 % compared to the baseline model when handling unconventional or inaccurately expressed user requirements. Finally, using the air conditioning domain as a case study, the effectiveness of the framework in achieving precise supply-demand cognition and customized product recommendations is validated through the Req2Sol-QAS system developed by invoking Req2Sol services.