Buch, Englisch, Band 734, 160 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 424 g
Buch, Englisch, Band 734, 160 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 424 g
Reihe: Lecture Notes in Electrical Engineering
ISBN: 978-3-030-66102-1
Verlag: Springer International Publishing
This book includes the proceedings of the second workshop on recommender systems in fashion and retail (2020), 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, or size and fit recommendations, and social media-influenced recommendations (outfits worn by influencers).
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Fachgebiete
- Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management E-Commerce, E-Business, E-Marketing
- Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Mathematik | Informatik EDV | Informatik Informatik Bildsignalverarbeitung
- Technische Wissenschaften Maschinenbau | Werkstoffkunde Technische Mechanik | Werkstoffkunde
Weitere Infos & Material
Chapter 1. The Importance of Brand A?nity in Luxury Fashion Recommendations.- Chapter 2. Probabilistic Color Modelling of Clothing Items.- Chapter 3. User Aesthetics Identi?cation for Fashion Recommendations.- Chapter 4. Towards User-in-the-Loop Online Fashion Size Recommendation with Low Cognitive Load.- Chapter 5. Attention Gets You the Right Size and Fit in Fashion.- Chapter 6. The Ensemble-Building Challenge for Fashion Recommendation.- Chapter 7. Out?t Generation and Recommendation – An Experimental Study.- Chapter 8. Understanding Professional Fashion Stylists' Outfit Recommendation Process.