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Recommender systems in fashion and r...

Dokoohaki, Nima.

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Recommender systems in fashion and retail

Record Type:	Electronic resources : Monograph/item
Title/Author:	Recommender systems in fashion and retail/ edited by Nima Dokoohaki ... [et al.].
other author:	Dokoohaki, Nima.
Published:	Cham :Springer International Publishing : : 2021.,
Description:	v, 160 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Recommender systems (Information filtering) -
Online resource:	https://doi.org/10.1007/978-3-030-66103-8
ISBN:	9783030661038

Recommender systems in fashion and retail
Recommender systems in fashion and retail[electronic resource] /edited by Nima Dokoohaki ... [et al.]. - Cham :Springer International Publishing :2021. - v, 160 p. :ill., digital ;24 cm. - Lecture notes in electrical engineering,v.7341876-1100 ;. - Lecture notes in electrical engineering ;v.734..

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)

ISBN: 9783030661038

Standard No.: 10.1007/978-3-030-66103-8doiSubjects--Topical Terms:

1002434
Recommender systems (Information filtering)

LC Class. No.: Q325.5 / .R436 2021

Dewey Class. No.: 025.04

Recommender systems in fashion and retail
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245 0 0 $a Recommender systems in fashion and retail $h [electronic resource] / $c edited by Nima Dokoohaki ... [et al.].
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a v, 160 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes in electrical engineering, $x 1876-1100 ; $v v.734
505 0 $a 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.
520 $a 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)
650 0 $a Recommender systems (Information filtering) $3 1002434
650 0 $a Fashion merchandising $x Data processing. $3 3332975
650 0 $a Human-computer interaction. $3 560071
650 0 $a Machine learning. $3 533906
650 1 4 $a Data Mining and Knowledge Discovery. $3 898250
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a e-Commerce/e-business. $3 1005486
650 2 4 $a Structural Materials. $3 898417
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 890871
700 1 $a Dokoohaki, Nima. $3 3380391
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830 0 $a Lecture notes in electrical engineering ; $v v.734. $3 3493220
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950 $a Mathematics and Statistics (SpringerNature-11649)