RecSys Challenge 2022数据集:Dressipi 1M时尚会议

Nick Landia, Rachael Mcalister, Donna North, Saikishore Kalloori, Abhishek Srivastava, B. Ferwerda
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引用次数: 3

摘要

作为RecSys挑战2022的一部分,Dressipi 1M时尚会议数据集公开发布。本文概述了数据集的内容和结构,并解释了构建数据集的过程。该数据集包含匿名浏览会话、每个会话的购买以及项目的内容数据。内容数据由代表物品描述性时尚特征的id组成,并使用Dressipi的human-in-the-loop标签系统进行分配。我们希望这个数据集在RecSys挑战之外的推荐系统研究中有价值,并鼓励更多时尚领域的出版物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RecSys Challenge 2022 Dataset: Dressipi 1M Fashion Sessions
As part of the RecSys Challenge 2022, the Dressipi 1M Fashion Sessions dataset is publicly released. This paper gives an overview of the content and structure of the dataset, as well as explaining the process by which it was constructed. The dataset contains anonymous browsing sessions, a purchase for each session, as well as content data of the items. The content data consists of IDs that represent descriptive fashion characteristics of the items and have been assigned using Dressipi’s human-in-the-loop labelling system. We hope that this dataset will be valuable in recommender systems research beyond the RecSys Challenge and encourage more publications in the fashion domain.
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