{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/sigir-2021-e-commerce-workshop-data-challenge","title":"SIGIR 2021 E-Commerce Workshop Data Challenge","arxiv_id":"2104.09423","date":"2021-04-19","proceeding":null,"authors":["Jacopo Tagliabue","Ciro Greco","Jean-Francis Roy","Bingqing Yu","Patrick John Chia","Federico Bianchi","Giovanni Cassani"],"abstract":"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.","url_abs":"https://arxiv.org/abs/2104.09423v4","url_pdf":"https://arxiv.org/pdf/2104.09423v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"sigir-2021-e-commerce-workshop-data-challenge","repo_url":"https://github.com/coveooss/SIGIR-ecom-data-challenge","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"sigir-2021-e-commerce-workshop-data-challenge","repo_url":"https://github.com/jacopotagliabue/metaflow-intent-prediction","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"sigir-2021-e-commerce-workshop-data-challenge","repo_url":"https://github.com/jacopotagliabue/you-dont-need-a-bigger-boat","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[],"methods":[],"datasets_introduced":[{"slug":"coveo-data-challenge-dataset","name":"Coveo Data Challenge Dataset","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}