WAYFAIR_WANDS_DATASET

WANDS is a Wayfair product search relevance dataset that is published as a companion to the paper from ECIR 2022:

WANDS: Dataset for Product Search Relevance Assessment
Yan Chen, Shujian Liu, Zheng Liu, Weiyi Sun, Linas Baltrunas and Benjamin Schroeder

The dataset allows objective benchmarking and evaluation of search engines on an E-Commerce dataset. Key features of this dataset includes:

42,994 candidate products
480 queries
233,448 (query,product) relevance judgements
Please refer to the paper for more details.