{"url":"/dataset/coveo-data-challenge-dataset","name":"Coveo Data Challenge Dataset","full_name":null,"description_markdown":"The 2021 SIGIR workshop on eCommerce is hosting the Coveo Data Challenge for \"In-session prediction for purchase intent and recommendations\". The challenge addresses the growing need for reliable predictions within the boundaries of a shopping session, as customer intentions can be different depending on the occasion. The need for efficient procedures for personalization is even clearer if we consider the e-commerce landscape more broadly: outside of giant digital retailers, the constraints of the problem are stricter, due to smaller user bases and the realization that most users are not frequently returning customers. We release a new session-based dataset including more than 30M fine-grained browsing events (product detail, add, purchase), enriched by linguistic behavior (queries made by shoppers, with items clicked and items not clicked after the query) and catalog meta-data (images, text, pricing information). On this dataset, we ask participants to showcase innovative solutions for two open problems: a recommendation task (where a model is shown some events at the start of a session, and it is asked to predict future product interactions); an intent prediction task, where a model is shown a session containing an add-to-cart event, and it is asked to predict whether the item will be bought before the end of the session.","description_withheld":null,"homepage":"https://github.com/coveooss/SIGIR-ecom-data-challenge","introduced_date":"2021-04-19","introduced_date_note":null,"introduced_by":{"paper":"/paper/sigir-2021-e-commerce-workshop-data-challenge","title":"SIGIR 2021 E-Commerce Workshop Data Challenge","first_author":"Jacopo Tagliabue","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"},{"name":"Environment","url":"/datasets/modality/environment"}],"tasks":[{"name":"Product Recommendation","url":"/task/product-recommendation","datasets_with_task":"/datasets/task/product-recommendation"}],"languages":[],"variants":["Coveo Data Challenge Dataset"],"data_loaders":[],"num_papers_in_archive":3,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/product-recommendation-on-coveo-data","task":"Product Recommendation","dataset_variant":"Coveo Data Challenge Dataset","rows":1,"metrics":["F1","MRR"],"first_row_in_archive_order":{"model":"Ensemble (60 models)","paper":"/paper/transformers-with-multi-modal-features-and","metrics":{"F1":"0.0748","MRR":"0.2784"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/transformers-with-multi-modal-features-and","title":"Transformers with multi-modal features and post-fusion context for e-commerce session-based recommendation","date":"2021-07-11","rows_on_this_dataset":1,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}