AI 中文总结
该文介绍TREC 2025产品搜索与推荐赛道，其含查询扩展与相关产品推荐任务，提供标注产品关系数据集，相关数据可支撑会话式产品发现等应用。
AI 中文摘要
过去几年，消费者已将大部分产品探索与购买活动转移至线上，以此获得线下购物难以企及的速度、便利性与便捷的价格对比。随着产品目录的多样性与规模不断增长，产品搜索与推荐已成为电商网站的核心支柱。尽管搜索引擎在电商中应用广泛，但目前仍缺乏用于评估端到端检索质量的高质量数据集。2025年，我们举办了TREC 2023与TREC 2024产品搜索赛道的修订延续版本。2025年产品搜索赛道包含两项任务：查询扩展与相关产品推荐。其中相关产品推荐任务颇具创新性，提供了标注的产品关系数据集，可区分互补产品与关联产品。我们预计该赛道产生的数据将为更好的推荐与搜索应用提供支撑，以反映用户需求，作为会话式产品发现体验的构建模块。
英文摘要
In the past few years, consumers have moved the bulk of their product exploration and purchasing efforts online seeking speed, convenience, and price comparison with ease unimaginable for in-person shopping. As product catalogs have grown in diversity and size product search and recommendation have become a cornerstone for e-commerce sites. Despite the widespread usage of search engines in e-commerce, there is no high-quality dataset designed to evaluate end-to-end retrieval quality. In 2025, we ran a revised and continued version of the Product Search track previously run at TREC 2023 and TREC 2024. The 2025 product search track had two tasks: query expansion and related-product recommendation. The related-product recommendation task is particularly novel, providing an annotated data set of product relationships that distinguishes between complementary and related products. We anticipate the data from this track will enable better recommendation and search applications that reflect user needs, as a building block for conversational product discovery experiences.
