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Recommender systems in fashion and retail : proceedings of the fourth Workshop at the Recommender Systems Conference (2022) / edited by Humberto Jesús Corona Pampín, Reza Shirvany.
ACM Conference on Recommender Systems (4th : 2022); Pampín, Humberto Jesús Corona, editor.; Shirvany, Reza, editor.
2023
ZA3084
Available Online
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Title
Recommender systems in fashion and retail : proceedings of the fourth Workshop at the Recommender Systems Conference (2022) / edited by Humberto Jesús Corona Pampín, Reza Shirvany.
Meeting Name
ACM Conference on Recommender Systems (4th : 2022)
ISBN
9783031221927 (electronic bk.)
3031221923 (electronic bk.)
9783031221910
3031221915
DOI
https://doi.org/10.1007/978-3-031-22192-7
Published
Cham : Springer, 2023.
Language
English
Description
1 online resource (121 pages) : illustrations (colour).
Item Number
10.1007/978-3-031-22192-7 doi
Call Number
ZA3084
Dewey Decimal Classification
005.5/6
Summary
This book includes the proceedings of the fourth workshop on recommender systems in fashion and retail (2022), and it aims to present a state-of-the-art view of the advancements within the field of recommendation systems with focused application to e-commerce, retail, and fashion by presenting readers with chapters covering contributions from academic as well as industrial researchers active within this emerging new field. Recommender systems are often used to solve different complex problems in this scenario, such as product recommendations, size and fit recommendations, and social media-influenced recommendations (outfits worn by influencers).
Note
Conference proceedings.
Access Note
Access limited to authorized users.
Source of Description
Description based on print version record.
Added Author
Pampín, Humberto Jesús Corona, editor.
Shirvany, Reza, editor.
Series
Lecture notes in electrical engineering ; v. 981.
Available in Other Form
Recommender systems in fashion and retail.
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1. Identification of Fine-grained Fit Information from Customer Reviews in Fashion
2. Personalization through User Attributes for Transformer-based Sequential Recommendation
3. Reusable Self-Attention-based Recommender System for Fashion
4. Adversarial Attacks against Visually-aware Fashion Outfit Recommender Systems
5. Contrastive Learning for Topic-Dependent Image Ranking
6. A Dataset for Learning Graph Representations to Predict Customer Returns in Fashion Retail
7. End-to-End Image-Based Fashion Recommendation.

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