TREC 2025发布新品搜索与推荐数据集，助力电商精准推荐。
Overview of the TREC 2025 Product Search and Recommendation Track
- 构建端到端产品搜索评估数据集，含查询扩展与关联推荐任务。
- 首次标注互补与相关商品关系，支持更智能的推荐系统。
- 适合研究电商推荐、对话式发现与评价基准的学者和工程师。
近年来，消费者将大部分产品探索与购买行为转移至线上，追求速度、便利性与价格对比。随着商品目录日益多样化和庞大，产品搜索与推荐已成为电商平台的核心功能。尽管搜索引擎在电商中广泛应用，但缺乏高质量的端到端检索评估数据集。2025年，我们延续TREC 2023与TREC 2024的产品搜索赛道，推出修订版新版本。该赛道包含两个任务：查询扩展与关联商品推荐。其中，关联商品推荐任务尤为创新，提供了标注了商品间关系的数据集，明确区分互补品与相关品。我们期望该数据集能推动更贴合用户需求的推荐与搜索应用发展，为对话式商品发现体验提供基础支撑。
原文摘要 · Abstract (English)
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.
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