João Gomes. 2017. Boosting Recommender Systems with Deep Learning. Association for Computing Machinery (ACM), 344–344. https://doi.org/10.1145/3109859.3109926

Digital Library

Google Scholar

[4]

Diogo Goncalves, Farfetch Liwei Liu, Farfetch João Sá, Farfetch Tiago Otto, Farfetch Ana Magalhães, Farfetch Paula Brochado, Liwei Liu, João Sá, Tiago Otto, Ana Magalhães, and Paula Brochado. 2020. The importance of brand affinity in luxury fashion recommendations.

Google Scholar

[5]

Diogo Goncalves, Liwei Liu, and Ana Magalhães. 2019. How big can style be? Addressing high dimensionality for recommending with style. (8 2019). http://arxiv.org/abs/1908.10642

Google Scholar

[6]

Liwei Liu, Ivo Silva, Pedro Nogueira, Ana Magalhães, and Eder Martins. 2020. User Aesthetics Identification for Fashion Recommendations. Recommender Systems in Fashion and Retail(2020), 41–58.

Google Scholar

[7]

Ana Magalhães. 2019. The trinity of luxury fashion recommendations: data, experts and experimentation. Industry Sessions at RecSys’19(2019).

Google Scholar

[8]

Pedro Nogueira, Diogo Gonçalves, Vanessa Marinho, Ana Magalhães, and João Sá. 2021. A critical analysis of offline evaluation decisions against online results: A real-time recommendations case study; A critical analysis of offline evaluation decisions against online results: A real-time recommendations case study.

Google Scholar

[9]

João Sá, Vanessa Queiroz Marinho, Ana Rita Magalhães, Tiago Lacerda, and Diogo Goncalves. 2022. Diversity Vs Relevance: A Practical Multi-objective Study in Luxury Fashion Recommendations. (2022). https://doi.org/10.1145/3477495.3531866

Digital Library

Google Scholar

Index Terms

Recommendations: They’re in fashion
1. Computer systems organization
  1. Dependable and fault-tolerant systems and networks
    1. Redundancy
  2. Embedded and cyber-physical systems
    1. Embedded systems
    2. Robotics
2. Networks
  1. Network properties
    1. Network reliability

Recommendations

The trinity of luxury fashion recommendations: data, experts and experimentation
RecSys '19: Proceedings of the 13th ACM Conference on Recommender Systems

Farfetch is the leading platform for online luxury fashion shopping. We have more than 3000 brands and high-end designers with the biggest catalog of luxury products available worldwide to more than 1 million customers.

The high-end luxury fashion ...
Brand competition in fashion e-commerce

Application of regression analysis to examine substitution effects in fashion e-commerce.Unexpectedly small extent of brand competition present in fashion e-commerce.Patterns and magnitude of cross-price effects are very distinct.Asymmetric competition ...
Recommendation system development for fashion retail e-commerce
Highlights
- Develop a real-world recommender for a large Korean fashion company.
- Extend ...
Abstract
This study presents a real-world collaborative filtering recommendation system implemented in a large Korean fashion company that sells fashion products through both online and offline shopping malls. The company’s recommendation ...

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RecSys '22: Proceedings of the 16th ACM Conference on Recommender Systems

September 2022

743 pages

ISBN:9781450392785

DOI:10.1145/3523227

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 13 September 2022

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RecSys '22

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RecSys '22: Sixteenth ACM Conference on Recommender Systems

September 18 - 23, 2022

WA, Seattle, USA

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Overall Acceptance Rate 254 of 1,295 submissions, 20%

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Index Terms

Recommendations

The trinity of luxury fashion recommendations: data, experts and experimentation

Brand competition in fashion e-commerce

Recommendation system development for fashion retail e-commerce

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