Fashion is a multi-billion-dollar industry with social and economic implications worldwide. One of the biggest problems confounding several fashion houses is the problem of unsold dead inventory. Despite having vast amounts of historical data pertaining to product, sales and inventory, only about 50-60% of the products sell well and rest go through severe mark downs. This is primarily due to volatile nature of fashion trends and fashion brands producing several new products to catch up with the trend. Fashion, i.e., “prevailing style during a particular time”, by design and definition changes by season, and so any unsold inventory at the end of each season is generally liquidated. While smaller designers and retailers generally move the merchandise to discount stores, some top design houses resort to recycling or even destroying the merchandise to avoid dilution of their brand. The environmental impact of the industry is even worse with the US EPA estimating 16 million tons of textile waste generated in 2016 in just the US.
Behind many fashion brands is a highly complex supply chain. Unsold merchandise/inventory is mainly due to mismatch between supply and demand. It could be that the inventory has been over-produced or not distributed properly at the right location and at the right time, mainly due to inaccurate demand forecastsand inefficiencies in supply chain planning. With the advent of modern AI technologies and vast amounts of (structured and unstructured) fashion data the impact on the fashion industry could be transformational and eventually enable intelligent self-correcting sustainable supply chains so that excess inventory is minimized.
The stakes are high for fast-fashion retailers and the insights provided by data can help facilitate earlier trend detection and more accurate demand forecasts to help build a more flexible and faster supply chain that reacts to market trends, manage assortment and inventory tuned to the local tastes and set prices and markdown optimally.
The goal of this workshop is to gather people from academia, industry, and startups working at the intersection of fashion, AI, data mining and knowledge discovery, and supply chain to further the technology and its adoption. The first, second, third and fourth international workshops on fashion and KDD were organized at KDD 2016 in San Francisco, KDD 2017 in Halifax, KDD2018 in London and KDD 220 in Anchorage respectively, and engendered scholarly debate among experts and led to several innovative ideas.
This year, responding to attendee feedback and increasing focus on responsible and sustainable supply chains, we are pivoting the workshop more towards the entire fashion supply/value chain rather than just the consumer facing use-cases. Indeed, in January 2020, the World Economic Forum Annual Meeting in Davos, Switzerland also recognized the growing importance of building more sustainable supply chains.
We hope this workshop will bring together all the researchers, practitioners, and interested audiences to explore the open problems, applications, and future directions in this field. We believe that the fashion industry introduces several interesting learning problems that are either not studied or scarcely studied in the past and can attract great interest in the general KDD community given their practical implications. Suggested topics include but are not limited to
We solicit submission of papers of papers of 4 to 10 pages representing reports of original research, preliminary research results, case studies, proposals for new work and position papers. We also seek poster submissions based on recently published work (please indicate the conference published).
All papers will be peer reviewed, single blind (i.e. author names and affiliations should be listed). If accepted, at least one of the authors must attend the workshop to present the work. The submitted papers must be written in English and formatted in the double column standard according to the ACM Proceedings Template, Tighter Alternate style. The papers should be in PDF format and submitted via the EasyChair submission site. The workshop website will archive the published papers.
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All deadlines are at 11:59 PM Pacific Standard Time.Submit