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Recommender systems in fashion and r...
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ACM Conference on Recommender Systems (2022))
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Recommender systems in fashion and retail = proceedings of the Fourth Workshop at the Recommender Systems Conference (2022) /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Recommender systems in fashion and retail/ edited by Humberto Jesus Corona Pampín, Reza Shirvany.
Reminder of title:
proceedings of the Fourth Workshop at the Recommender Systems Conference (2022) /
other author:
Pampin, Humberto Jesus Corona.
corporate name:
ACM Conference on Recommender Systems
Published:
Cham :Springer Nature Switzerland : : 2023.,
Description:
ix, 119 p. :ill., digital ;24 cm.
[NT 15003449]:
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.
Contained By:
Springer Nature eBook
Subject:
Recommender systems (Information filtering) - Congresses. -
Online resource:
https://doi.org/10.1007/978-3-031-22192-7
ISBN:
9783031221927
Recommender systems in fashion and retail = proceedings of the Fourth Workshop at the Recommender Systems Conference (2022) /
Recommender systems in fashion and retail
proceedings of the Fourth Workshop at the Recommender Systems Conference (2022) /[electronic resource] :edited by Humberto Jesus Corona Pampín, Reza Shirvany. - Cham :Springer Nature Switzerland :2023. - ix, 119 p. :ill., digital ;24 cm. - Lecture notes in electrical engineering,v. 9811876-1119 ;. - Lecture notes in electrical engineering ;v. 981..
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.
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)
ISBN: 9783031221927
Standard No.: 10.1007/978-3-031-22192-7doiSubjects--Topical Terms:
3221329
Recommender systems (Information filtering)
--Congresses.
LC Class. No.: ZA3084
Dewey Class. No.: 005.56
Recommender systems in fashion and retail = proceedings of the Fourth Workshop at the Recommender Systems Conference (2022) /
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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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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)
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based on 0 review(s)
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W9452520
電子資源
11.線上閱覽_V
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EB ZA3084
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