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基于LLM特征提取的多准则库存分类
原标题：LLM-Based Feature Extraction for Multi-Criteria Inventory Classification
AI 摘要
该论文提出一种基于LLM的特征提取方法，将客户评论等非结构化数据通过向量嵌入和LLM生成的评估标准转化为定量特征，并融入基于Hadi-Vencheh模型的多准则库存分类（MCIC）框架。实验显示，加入客户情感信号后库存分类出现可测量的重分类效果，表明非结构化数据可增强库存优先级排序。
以上摘要由 AI 生成，可能存在误差。事实请以原文为准。
正文节选
LLM-Based Feature Extraction for Multi-Criteria Inventory Classification Abstract E-commerce supply chains generate large volumes of customer feedback and operational data that remain underutilized in inventory management. Traditional inventory classification techniques such as ABC analysis rely primarily on annual dollar usage, while multi-criteria inventory classification (MCIC) methods extend this but still depend on structured quantitative data and do not utilize unstructured information ava
发布时间：2026-11-10 13:00
抓取时间：2026-11-09 13:08
来源机构：arXiv