---

＜電子ブック＞
Recommender Systems in Fashion and Retail / edited by Nima Dokoohaki, Shatha Jaradat, Humberto Jesús Corona Pampín, Reza Shirvany
(Lecture Notes in Electrical Engineering. ISSN:18761119 ; 734)

版	1st ed. 2021.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2021
本文言語	英語
大きさ	V, 160 p. 52 illus., 45 illus. in color : online resource
著者標目	Dokoohaki, Nima editor Jaradat, Shatha editor Corona Pampín, Humberto Jesús editor Shirvany, Reza editor SpringerLink (Online service)
件　名	LCSH:Data mining LCSH:Artificial intelligence LCSH:Computational intelligence LCSH:Electronic commerce LCSH:Building materials LCSH:Image processing FREE:Data Mining and Knowledge Discovery FREE:Artificial Intelligence FREE:Computational Intelligence FREE:e-Commerce and e-Business FREE:Wood, fabric, and textiles FREE:Image Processing
一般注記	Chapter 1. The Importance of Brand Affinity in Luxury Fashion Recommendations -- Chapter 2. Probabilistic Color Modelling of Clothing Items -- Chapter 3. User Aesthetics Identification 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. Outfit Generation and Recommendation – An Experimental Study -- Chapter 8. Understanding Professional Fashion Stylists' Outfit Recommendation Process 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). HTTP:URL=https://doi.org/10.1007/978-3-030-66103-8

 類似資料