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KDD 2020 workshop - AI for Fashion Supply Chain : The fifth international workshop on fashion and KDD

San Diego, CA, USA
Event Date: Aug 24, 2020 - Aug 24, 2020
Submission Deadline: May 20, 2020
Notification of Acceptance: Jun 15, 2020

About

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.

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.

Call For Paper

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

  • AI for fashion supply/value chain
  • Deep learning for fashion
  • Sales and demand forecasting
  • Improved forecasting incorporating external events like weather, events etc.
  • Attribute based demand forecasting
  • New product demand forecasting
  • Spatial-temporal hyper-local demand forecasting 
  • New stores sales forecasting
  • Demand transference models 
  • Discrete choice models
  • Trend analysis and forecasting
  • Sentiment analysis
  • Hyper-local assortment planning
  • Inventory allocation 
  • Store clustering
  • Inventory policies  and dynamic auto-replenishment
  • Markdown optimization 
  • Stock re-allocation and inter store transfer 
  • Algorithmic product design 
  • Omni-channel order fulfillment and inventory planning
  • Visual search for fashion e-commerce
  • Fashion image understanding and auto-tagging of apparel
  • Virtual personal fashion assistants
  • Recommendation engines for fashion
  • AI tools for fashion designers, buyers, merchandisers, and consumers
  • Sustainable supply chains
  • Improving provenance and trust in the fashion supply chain
  • Circular economy and methods and policies to encourage reuse and recycling of materials
  • Handling disruptions in fashion supply chain 
  • Ideas from other industries with rapid obsolescence

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