AI辅助电商售后工单自动分类

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电商客服工单分类

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利用自然语言处理技术，对电商平台用户提交的售后咨询与投诉工单进行语义分析与意图识别，自动归类至物流、质量或退款等具体业务模块，以提升客服响应效率与处理准确率。

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Analyze the following e-commerce customer support ticket text to identify the core issue and determine its business category. The content involves common scenarios such as damaged goods, delayed shipping, or refund requests. Extract key entities like order numbers, product names, and problem descriptions. Map the ticket to the most appropriate category based on predefined standards including logistics issues, product quality, after-sales service, and others. If the user expresses strong emotions or uses sensitive language, flag it as high priority. The final output should include the classification result, confidence score, and brief handling suggestions, ensuring clear logic that aligns with actual business operations to help the customer service team quickly triage and prioritize urgent cases.

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请分析以下电商用户提交的售后工单文本，识别其核心诉求并判断所属业务类别。工单内容涉及商品破损、物流延误或退款申请等常见场景。你需要提取关键实体如订单号、商品名称及问题描述，根据预设的分类标准（包括物流问题、产品质量、售后服务、其他）将工单映射至最匹配的类别。若用户情绪激动或包含敏感词汇，需标记为高优先级。最终输出应包含分类结果、置信度评分及简要的处理建议，确保分类逻辑清晰且符合实际业务操作规范，帮助客服团队快速分流并优先处理紧急案件。

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