Description

Book Synopsis

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).



Table of Contents
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 Offline Evaluation Decisions Against Online Results: A Real-Time Recommendations Case Study.- Chapter 6. Attentive Hierarchical Label Sharing for Enhanced Garment and Attribute Classification of Fashion Imagery.- Chapter 7. Style-based Interactive Eyewear Recommendations.

Recommender Systems in Fashion and Retail:

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    A Hardback by Nima Dokoohaki, Shatha Jaradat, Humberto Jesús Corona Pampín

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      Publisher: Springer Nature Switzerland AG
      Publication Date: 08/03/2022
      ISBN13: 9783030940157, 978-3030940157
      ISBN10: 3030940152

      Description

      Book Synopsis

      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).



      Table of Contents
      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 Offline Evaluation Decisions Against Online Results: A Real-Time Recommendations Case Study.- Chapter 6. Attentive Hierarchical Label Sharing for Enhanced Garment and Attribute Classification of Fashion Imagery.- Chapter 7. Style-based Interactive Eyewear Recommendations.

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