RecSys Challenge 2022 Dataset: Dressipi 1M Fashion Sessions
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Author / Producer
Date
2022-09
Publication Type
Conference Paper
ETH Bibliography
yes
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Data
Abstract
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.
Permanent link
Publication status
published
External links
Editor
Book title
RecSysChallenge '22: Proceedings of the Recommender Systems Challenge 2022
Journal / series
Volume
Pages / Article No.
1 - 3
Publisher
Association for Computing Machinery
Event
ACM Recommender Systems Challenge Workshop (RecSys Challenge 2022)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Session-based; Competition; Dataset; Fashion Recommendation; Recommender systems
Organisational unit
02154 - Media Technology Center (MTC) / Media Technology Center (MTC)