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Recommender systems in fashion and retail / Nima Dokoohaki, Shatha Jaradat, Humberto Jesús Corona Pampín, Reza Shirvany, editors.

Dokoohaki, Nima, editor.; Jaradat, Shatha, editor.; Corona Pampín, Humberto Jesús, editor.; Shirvany, Reza, editor.
2021
ZA3084
Available Online
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Title
Recommender systems in fashion and retail / Nima Dokoohaki, Shatha Jaradat, Humberto Jesús Corona Pampín, Reza Shirvany, editors.
ISBN
9783030661038 (electronic book)
3030661032 (electronic book)
3030661024
9783030661021
DOI
https://doi.org/10.1007/978-3-030-66103-8
Published
Cham, Switzerland : Springer, [2021]
Language
English
Description
1 online resource.
Item Number
10.1007/978-3-030-66103-8 doi
Call Number
ZA3084
Dewey Decimal Classification
025.04
006.3/1
Summary
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).
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed April 5, 2021).
Added Author
Dokoohaki, Nima, editor.
Jaradat, Shatha, editor.
Corona Pampín, Humberto Jesús, editor.
Shirvany, Reza, editor.
Series
Lecture notes in electrical engineering ; v. 734.
Available in Other Form
Print version: 9783030661021
Linked Resources
Online Access
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All Resources
The Importance of Brand Afinity in Luxury Fashion Recommendations
Probabilistic Color Modelling of Clothing Items
User Aesthetics Identification for Fashion Recommendations
Towards User-in-the-Loop Online Fashion Size Recommendation with Low Cognitive Load
Attention Gets You the Right Size and Fit in Fashion
The Ensemble-Building Challenge for Fashion Recommendation: Investigation of In-Home Practices and Assessment of Garment Combinations
Outfit Generation and Recommendation: An Experimental Study
Understanding Professional Fashion Stylists' Outfit Recommendation Process: A Qualitative Study.

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