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FashionXRecsys -
Workshop on Recommender Systems in Fashion
In
conjunction with ACM RecSys 2020 (26th September 2020)
**Important
Note** Due to
concerns about COVID-19, RecSys 2020 will cancel its
physical component and go fully virtual.
We
are pleased to invite you to participate in the 2nd workshop
on Recommender Systems in Fashion (FashionXRecsys) that will
be held on September 26th, 2020.
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):
*
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.)
In
order to encourage the reproducibility of research work
presented in the workshop, we put together a list of open
datasets in the fashionXrecsys website. All
submissions that present their work using at least one of
the listed datasets will be considered for the best paper,
best student paper and best demo awards, which will be given
by workshop sponsors.
Important
Dates
*
Paper Submission deadline: July 29th, 2020
*
Author notification: August 21st, 2020
*
Camera-ready version deadline: September 4th,2020
All
deadlines refer to 23:59 (11:59pm) in the AoE (Anywhere on
Earth) time zone.
Paper
Submission Instructions
*
Submissions should be prepared according to the ACM RecSys format. 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.
*
The peer review process is double-blind (i.e. anonymised).
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.
*
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 attend the workshop and
present their work. 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, and will be
published in a special Springer Journal issue.
Additional
Submission Instructions for Demos
*
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. (This section will be removed for
the camera-ready version of accepted contributions.)
Kindest
Regards,
FashionXRecsys
Organizers