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© 2021

Recommender Systems in Fashion and Retail

  • Nima Dokoohaki
  • Shatha Jaradat
  • Humberto Jesús Corona Pampín
  • Reza Shirvany
Conference proceedings
  • 1.7k Downloads

Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 734)

Table of contents

  1. Front Matter
    Pages i-v
  2. Fashion Understanding

    1. Front Matter
      Pages 1-1
    2. Diogo Goncalves, Liwei Liu, João Sá, Tiago Otto, Ana Magalhães, Paula Brochado
      Pages 3-19
    3. Mohammed Al-Rawi, Joeran Beel
      Pages 21-40
    4. Liwei Liu, Ivo Silva, Pedro Nogueira, Ana Magalhães, Eder Martins
      Pages 41-55
  3. Sizing and Fit in Online Fashion

    1. Front Matter
      Pages 57-57
    2. Leonidas Lefakis, Evgenii Koriagin, Julia Lasserre, Reza Shirvany
      Pages 59-76
    3. Karl Hajjar, Julia Lasserre, Alex Zhao, Reza Shirvany
      Pages 77-98
  4. Combining Fashion

    1. Front Matter
      Pages 99-99
    2. Marjan Celikik, Matthias Kirmse, Timo Denk, Pierre Gagliardi, Sahar Mbarek, Duy Pham et al.
      Pages 117-137

About these proceedings

Introduction

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).  

Keywords

Recommender Systems Information Retrieval Information Systems Machine Learning AI Artificial Intelligence Computer Vision Text Mining Fashion Retail E-commerce

Editors and affiliations

  • Nima Dokoohaki
    • 1
  • Shatha Jaradat
    • 2
  • Humberto Jesús Corona Pampín
    • 3
  • Reza Shirvany
    • 4
  1. 1.KTH - Royal Institute of TechnologyStockholmSweden
  2. 2.KTH - Royal Institute of TechnologyStockholmSweden
  3. 3.Machine Learning PlatformBooking.comAmsterdamThe Netherlands
  4. 4.Digital Experience-AI & Builder PlatformZalando SEBerlinGermany

Bibliographic information

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