Workshop on Recommender Systems in Fashion

Online Fashion retailers have significantly increased in popularity over the last decade, making it possible for customers to explore hundreds of thousands of products without the need to visit multiple stores or stand in long queues for checkout. However, the customers still face several hurdles with current online shopping solutions. For example, customers often feel overwhelmed with the large selection of the assortment and brands. In addition, there is still a lack of effective suggestions capable of satisfying customers’ style preferences, or size and fit needs, necessary to enable them in their decision-making process. Moreover, in recent years social shopping in fashion has surfaced, thanks to platforms such as Instagram, providing a very interesting opportunity that allows to explore fashion in radically new ways. Such recent developments provides exciting challenges for Recommender Systems and Machine Learning research communities.

The first fashionXrecsys workshop aims to bring together researchers and practitioners in the fashion, recommendations and machine learning domains to discuss open problems in the area of fashion e-commerce and retail. To provide rich opportunities to share opinions and experience in such an emerging field, we will accept paper submissions on established and novel ideas, as well as new interactive participation formats.

Organizers
  • Shatha Jaradat, KTH Royal Institute of Technology, Sweden
  • Nima Dokoohaki, Accenture, Sweden
  • Humberto Corona, Zalando, Germany
  • Reza Shirvany, Zalando, Germany
Website

https://zalandoresearch.github.io/fashionxrecsys/

Date

Friday, Sept 20, 2019, 09:00-17:30

Location

Room 102

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