SAM-D2Q：将多模态Doc2Query与搜索需求及转化对齐的电商方案
SAM-D2Q: Aligning Multimodal Doc2Query with Search Demand and Conversion for E-commerce
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中文总结 AI 辅助
针对电商搜索的词汇不匹配问题，提出SAM-D2Q多模态文档扩展框架，经离线实验及速卖通部署验证，可提升检索性能并实现GMV与支付笔数增长。
中文摘要 AI 辅助
电商搜索常面临用户查询与商家生成的商品标题间的词汇不匹配问题，因为短标题无法完全覆盖多样的用户表达或商品视觉属性。虽然Doc2Query可通过生成伪查询来扩展文档以缓解该问题，但传统方法仅基于文本，未针对电商业务目标优化，可能生成语义合理但商业效果不佳的扩展结果，且会遗漏商品图像中的关键属性。为此，我们提出面向电商搜索的业务对齐多模态文档扩展框架SAM-D2Q，该框架需满足布尔检索约束，包含三个阶段：（1）任务适配的多模态监督微调，以增强对商品标题、图像及用户查询的视觉-语言理解；（2）多模态数据增强，提升对关键视觉属性的感知及扩展覆盖范围；（3）基于强化学习的偏好对齐，朝向搜索业务目标，鼓励模型生成更贴合用户意图与商业价值的伪查询。离线实验显示，SAM-D2Q较传统Doc2Query方法显著提升了检索性能；其在速卖通生产搜索系统中部署后，线上业务指标得到改善，GMV提升3.38%，支付笔数提升2.27%。
英文摘要
E-commerce search often suffers from vocabulary mismatch between user queries and merchant-authored product titles, since short titles cannot fully cover diverse user expressions or visual product attributes. Although Doc2Query alleviates this issue by generating pseudo-queries for document expansion, traditional methods are text-only and not optimized for e-commerce business objectives. As a result, they may produce semantically plausible but commercially ineffective expansions and miss key attributes present in product images. To this end, we propose E-commerce Search-Aligned Multimodal Doc2Query (SAM-D2Q), a business-aligned multimodal document expansion framework for e-commerce search under Boolean retrieval constraints. SAM-D2Q consists of three stages: (1) task-adapted multimodal supervised fine-tuning to enhance vision-language understanding of product titles, images, and user queries; (2) multimodal data augmentation to improve perception of key visual attributes and expansion coverage; and (3) reinforcement-learning-based preference alignment toward search business objectives, encouraging the model to generate pseudo-queries that better match user intent and commercial value. Offline experiments show that SAM-D2Q substantially improves retrieval performance over traditional Doc2Query methods. Deployed in the AliExpress production search system, SAM-D2Q improves online business metrics, increasing GMV by +3.38% and Pay Count by +2.27%.
发表机构
- Alibaba International Digital Commerce Group（阿里巴巴国际数字商业集团）
机构由 AI 辅助整理，请以论文原文为准。
