<html> <head> <meta http-equiv="Content-Type" content="text/html; charset=Windows-1252"> <style type="text/css" style="display:none;"></style> </head> <body dir="ltr"> <div id="divtagdefaultwrapper" dir="ltr" style="font-size: 12pt; color: rgb(0, 0, 0); font-family: Calibri, Helvetica, sans-serif, Helvetica, EmojiFont, "Apple Color Emoji", "Segoe UI Emoji", NotoColorEmoji, "Segoe UI Symbol", "Android Emoji", EmojiSymbols;"> CFP: <a href="https://fashionxrecsys.github.io/fashionxrecsys-2021/" style="">Workshop on Recommender Systems in Fashion & Retail</a> In conjunction with ACM RecSys 2021, Amsterdam, Netherlands, 27th September-1st October 2021 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. In this context, recommender systems are very well positioned to play a crucial role in creating a great customer experience in fashion. 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 provide exciting challenges for the Recommender Systems and Machine Learning research communities. 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 new 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. Suggested topics for submissions are (but not limited to): <ul style="margin-bottom:0px; margin-top:0px"> <li>Computer vision in Fashion (image classification, semantic segmentation, object detection)</li><li>Deep learning in recommendation systems for Fashion</li><li>Learning and application of fashion style (personalized style, implicit and explicit preferences, budget, social behaviour, etc) </li><li>Size and Fit recommendations through mining customers implicit and explicit size and fit preferences</li><li>Modelling articles and brands size and fit similarity</li><li>Usage of ontologies and article metadata in fashion and retail (NLP, social mining, search)</li><li>Addressing cold-start problem both for items and users in fashion recommendation</li><li>Knowledge transfer in multi-domain fashion recommendation systems</li><li>Hybrid recommendations on customers’ history and on-line behavior</li><li>Multi- or Cross- domain recommendations (social media and online shops)</li><li>Privacy preserving techniques for customer’s preferences tracing</li><li>Understanding social and psychological factors and impacts of influence on users’ fashion choices (such as Instagram, influencers, etc.) </li></ul> In order to encourage the reproducibility of research work presented in the workshop, we put together a list of open datasets in the <a href="https://fashionxrecsys.github.io/fashionxrecsys-2021/" style="">fashionXrecsys website</a>. All submissions present work evaluated in at least one of the described open datasets will be considered for the best paper, best student paper and best demo awards, which will be given by our sponsors. Mentorship This year we will continue to offer mentorship opportunities to students who would like to get initial feedback on their work by industry colleagues. We aim to increase the chances of innovative student’s work being published, as well as to foster an early exchange across academia and industry. As a mentee, you should expect at least one round of review of your work p r to the submission deadline. If your work is accepted, you should also expect at least one feedback session regarding your demo, poster or oral presentation. If you want to participate in the mentorship program, please <a href="https://fashionxrecsys.github.io/fashionxrecsys-2021/#footer" style="">get in touch via e-mail</a> Important Dates <ul style="margin-bottom:0px; margin-top:0px"> <li>Mentorship deadline: June 11th, 2021</li><li>Submission deadline: July 30th, 2021</li><li>Author notification: August 23st, 2021</li><li>Camera-ready version: September 6th 2021</li></ul> Paper Submission Instructions <ul style="margin-bottom:0px; margin-top:0px"> <li>All submissions and reviews will be handled electronically via EasyChair at the following address: <a href="https://easychair.org/conferences/?conf=fashionxrecsys21" style="background-color:transparent; font-family:Arial; font-size:10pt; white-space:pre">https://easychair.org/conferences/?conf=fashionxrecsys21</a></li><li>Submissions should be prepared according to the <a href="https://recsys.acm.org/recsys21/call/" style="background-color:transparent; font-family:Arial; font-size:10pt; white-space:pre">single-column ACM RecSys format</a>. Long papers should report on substantial contributions of lasting value. The maximum length is 14 pages (excluding references) in the new single-column format. For short papers, the maximum length is 7 pages (excluding references) in the new single-column format.</li><li>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, anonymise citations to your previous work 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 specifically necessary for understanding the work described in the paper.</li><li>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.</li><li>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.</li><li>All accepted papers will be available through the program website. Moreover, the workshop papers will be published in a Springer special issue.</li></ul> 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 <a href="https://recsys.acm.org/recsys21/call/#content-tab-1-5-tab" style="">RecSys 2021 Demos Call for Contributions</a>. The submission should include: <ul style="margin-bottom:0px; margin-top:0px"> <li>An overview of the algorithm or system that is the core of the demo, including citations to any publications that support the work..</li><li>A discussion of the purpose and the novelty of the demo.</li><li>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.)</li><li>A link to a narrated screen capture of your system in action, ideally a video (This section will be removed for the camera-ready version of accepted contributions)</li><li>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.</li></ul> For any inquiries and questions, please contact us: <a href="mailto:fashionxrecsys@gmail.com" style="">fashionxrecsys@gmail.com</a> Join the #fashion-recsys community in slack by <a href="https://recsys.acm.org/slack-invite/" style="">following these instructions</a> </div> </body> </html>