CFP: Workshop on Recommender Systems in Fashion & Retail

In conjunction with ACM RecSys 2023, Singapore, 18th-22nd September 2023

The workshop itself will be held virtually on September 18th 2023 at 2pm Singapore time

Submissions accepted until August 3rd 2023 Anywhere on Earth

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. Recommender Systems are often used to solve different complex problems in this domain, such as social fashion-aware recommendations (outfits inspired by influencers), product recommendations or size and fit recommendations. The fifth edition of this workshop aims at providing an avenue for continuing the discussion of novel approaches and applications of recommendation systems in fashion and e-commerce with a particular focus on pandemic and post-pandemic era events and their short and long lasting effects on e-commerce and Fashion.

This workshop aims to bring together researchers and practitioners in the fashion, recommendations and machine learning domains to discuss open problems in the aforementioned areas. This involves addressing interdisciplinary problems with all of the challenges it entails. Within this workshop we aim to start the conversation among professionals in the fashion and e-commerce industries and recommender systems scientists, and create a space for collaboration between these communities necessary for tackling these deep problems. 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.

Keynotes

This year we will have the pleasure of hosting Prof Calving Wong and Tian Su. Prof. Calvin Wong is currently the CEO and Centre Director of Laboratory for Artificial Intelligence in Design (AiDLab), a research platform jointly established by the Hong Kong Polytechnic University (PolyU) and Royal College of Art (RCA) in the UK. Tian Su is currently Vice-President eCommerce Platform at Zalando, the largest European ecommerce platform for Fashion including garments, shoes and beauty.

Important Dates 

• Paper submission deadline: August 3rd, 2023 Anywhere on Earth
• Review deadline: August 21st 2023
• Author notification: August 27th, 2023
• Camera-ready version: September 10th, 2023
• Workshop: September 18th or 19th (TBD), 2023

Suggested topics for submissions are (but not limited to):

• Pandemic era short on long term effects and potential solutions in Fashion recommendation systems)
• Computer vision in Fashion (image classification, semantic segmentation, object detection.)
• Deep learning in recommendation systems for Fashion.
• Learning and application of fashion style (personalized style, implicit and explicit preferences, budget, social behaviour, etc.)
• Size and Fit recommendations through mining customers implicit and explicit size and fit preferences.
• Modelling articles and brands size and fit similarity.
• Usage of ontologies and article metadata in fashion and retail (NLP, social mining, search.)
• Addressing cold-start problem both for items and users in fashion recommendation.
• Knowledge transfer in multi-domain fashion recommendation systems.
• Hybrid recommendations on customers’ history and on-line behavior.
• Multi- or Cross- domain recommendations (social media and online shops)
• Privacy preserving techniques for customer’s preferences tracing.
• Understanding social and psychological factors and impacts of influence on users’ fashion choices (such as Instagram, influencers, etc.)

Reproducibility

In order to encourage the reproducibility of research work presented in the workshop, we put together a list of open datasets in this website.

Paper Submission Instructions 

• All submissions and reviews will be handled electronically via EasyChair
• Submissions should be prepared according to the a single-column ACM RecSys format . We will consider both long and short papers. For long papers, the maximum length is 16 pages including appendices (plus up to 2 pages references). For short papers, the maximum length is 8 pages (plus up to 2 pages references).
• The peer review process is double-blind (i.e. anonymised). This means that all submissions must not include information identifying the authors or their organisation. Specifically, do not include the authors’ names and affiliations, refer to your previous work in the third person and avoid providing any other information that would allow to identify the authors, such as acknowledgments and funding. However, it is acceptable to explicitly refer in the paper to the companies or organizations that provided datasets, hosted experiments or deployed solutions if there is no implication that the authors are currently affiliated with the mentioned organization.
• Submitted work should be original. However, technical reports or ArXiv disclosure prior to or simultaneous with the workshop submission, is allowed, provided they are not peer-reviewed. The organizers also encourage authors to make their code and datasets publicly available.
• Accepted contributions are given either an oral or poster presentation slot at the workshop. At least one author of every accepted contribution must be registered and attend the workshop to present their work, either in-person or virtually. Please contact the workshop organization if none of the authors will be able to attend.
• All accepted papers will be available through the program website. Moreover, we are currently in conversations with Springer in order to publish the workshop papers in a special issue journal.

Additional Submission Instructions for Demos 

Submissions for extended abstract of demos should be prepared according to the standard double-column ACM SIG proceedings format as described in the RecSys 2023 Demos Call for Contributions . The submission should include:

• An overview of the algorithm or system that is the core of the demo, including citations to any publications that support the work..
• A discussion of the purpose and the novelty of the demo.
• A description of the required setup. If the system will feature an installable component (e.g., mobile app) or website for users to use throughout or after the conference, please mention this.
• A link to a narrated screen capture of your system in action, ideally a video. The maximum duration of screen capture is 10 minutes. (This section will be removed for the camera-ready version of accepted contributions but might be included in the virtual platform used to host the online part of the workshop.)
• We also highly encourage any external material related to the demo (e.g., shared code on GitHub). Please, provide a link to the shared code in the extended abstract accompanying the demo.

For any inquiries and questions, please contact julia.lasserre@zalando.de