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arXiv · 2608.17138

Overview of the TREC 2025 Product Search and Recommendation Track

Dean E. Alvarez·Surya Kallumadi·Daniel Campos·ChengXiang Zhai·Alessandro Magnani·Rikiya Takehi·Michael D. Ekstrand
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Abstract

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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Dean E. Alvarez, Surya Kallumadi, Daniel Campos, ChengXiang Zhai, Alessandro Magnani, Rikiya Takehi, Michael D. Ekstrand. 2026-08-17. Overview of the TREC 2025 Product Search and Recommendation Track. https://arxiv.org/abs/2608.17138

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