Recommender Systems in Fashion and Retail -

Recommender Systems in Fashion and Retail

Proceedings of the Third Workshop at the Recommender Systems Conference (2021)
Buch | Softcover
VI, 115 Seiten
2023 | 1st ed. 2022
Springer International Publishing (Verlag)
978-3-030-94018-8 (ISBN)
85,59 inkl. MwSt

This book includes the proceedings of the third workshop on recommender systems in fashion and retail (2021), 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).

Chapter 1. Using Relational Graph Convolutional Networks to Assign Fashion Communities to Users.- Chapter 2. What Users Want? WARHOL: A Generative Model for Recommendation.- Chapter 3. Knowing When You Don't Know in Online Fashion: An Uncertainty Aware Size Recommendation Framework.- Chapter 4. SkillSF: In the Sizing Game, Your Size is Your Skill.- Chapter 5. A Critical Analysis of O ine Evaluation Decisions Against Online Results: A Real-Time Recommendations Case Study.- Chapter 6. Attentive Hierarchical Label Sharing for Enhanced Garment and Attribute Classification of Fashion Imagery.- Chapter 7. Style-based Interactive Eyewear Recommendations.

Erscheinungsdatum
Reihe/Serie Lecture Notes in Electrical Engineering
Zusatzinfo VI, 115 p. 22 illus., 21 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 201 g
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Schlagworte AI Artificial Intelligence • computer vision • E-Commerce • fashion retail • Information Retrieval • information systems • machine learning • Recommender Systems • Text Mining
ISBN-10 3-030-94018-7 / 3030940187
ISBN-13 978-3-030-94018-8 / 9783030940188
Zustand Neuware
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