Fifth Workshop on Recommender Systems in Fashion and Retail-fashionXrecsys2023

被引：0

作者：

Lasserre, Julia ^{[1
]}

Dokoohaki, Nima ^{[2
]}

Shirvany, Reza ^{[1
]}

机构：

[1] Zalando SE, Berlin, Germany

[2] Accenture AI, Sophia Antipolis, France

来源：

PROCEEDINGS OF THE 17TH ACM CONFERENCE ON RECOMMENDER SYSTEMS, RECSYS 2023 | 2023年

关键词：

Recommendations; Fashion; E-Commerce; Social Networks; Deep Learning; Computer Vision; Outfit; Sizing; Fit;

D O I：

10.1145/3604915.3608753

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Online Fashion retailers have significantly increased in popularity over the last decade, making it possible for customers to explore hundreds of thousands of products without the need to visit multiple stores or stand in long queues for checkout. Recommender Systems are often used to solve different complex problems in this domain, such as social fashion-aware recommendations (outfits inspired by influencers), product recommendations, or size and fit recommendations. Moreover, the research interest on this area is increasing, demonstrated by the success of the past four editions of the fashionXrecsys workshops 2019 1 2020 2 2021 3 2022 4. The fifth edition of the workshop aims at providing an avenue for continuing the discussion of novel approaches and applications of recommendation systems in fashion and e-commerce with a particular focus on pandemic and post-pandemic era events and their short and long lasting effects on e-commerce and Fashion.

引用

页码：1237 / 1240

页数：4

共 7 条

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[2]

Dookohaki Nima., 2020, Fashion Recommender Systems

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Jaradat, Shatha ;

Dokoohaki, Nima ;

Pampin, Humberto Jesus Corona ;

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RECSYS 2020: 14TH ACM CONFERENCE ON RECOMMENDER SYSTEMS, 2020, :632-634

[4]

Jaradat Shatha, 2019, WORKSHOP RECOMMENDER, P552

[5]

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[6]

Jesus Humberto, 2022, 16 ACM C RECOMMENDER

[7]

Jesus Humberto, 2022, Recommender Systems in Fashion and Retail

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