Recommender Systems in Fashion and Retail

Proceedings of the Third Workshop at the Recommender Systems Conference (2021)
1. Auflage 2022
ISBN: 978-3-030-94015-7
Verlag: Springer International Publishing

Buch, Englisch, Band 830, 115 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 360 g

Reihe: Lecture Notes in Electrical Engineering

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).

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Dokoohaki, Nima

Shirvany, Reza

Jaradat, Shatha

Corona Pampín, Humberto Jesús

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaft und Gesellschaft | Kulturwissenschaften Populärkultur
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Digital Lifestyle Internet, E-Mail, Social Media
• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management E-Commerce, E-Business, E-Marketing
• Mathematik | Informatik EDV | Informatik Technische Informatik Computersicherheit Datensicherheit, Datenschutz
• Sozialwissenschaften Medien- und Kommunikationswissenschaften Kommunikationswissenschaften Digitale Medien, Internet, Telekommunikation

Inhaltsverzeichnis

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 Classi?cation of Fashion Imagery.- Chapter 7. Style-based Interactive Eyewear Recommendations.