In the talk, I will give brief overview of all the Machine Learning we do on E-commerce Catalog. In particular we will discuss Classification, Attribute Extraction, Matching/Mis-Match Detection, Base Variant Grouping, Title Optimization and Asset Optimization. Each of these ML application help enrich the product catalog & get structured data from unstructured text. I will do deep dive on Asset Optimization, as visual content such as product images is very critical for good customer experience. In e-commerce, product content, especially product images have a significant influence on a customer's journey from product discovery to evaluation and finally, purchase decision. We will be discussing in detail the following 2 research papers from my group:

 

(a) A Smart System for Selecting Optimal Product Images in Ecommerce  (https://arxiv.org/abs/1811.07996) :  I will present a machine learning driven - Visual Content Management system for extremely large e-commerce catalogs. I will explain how we decide which images to show to the customer for a particular product.

(b) Image Matters: Detecting Offensive and Non-Compliant Content / Logo in Product Images (https://arxiv.org/abs/1905.02234) :

 

I will present how we identify all offensive and non-compliant images like Nudity, Sexually Explicit, Racist, False Made in USA/Best Seller Logos, Assault Rifles, etc. Such images can severely damage the customer experience, lead to legal issues, and erode the company brand. We will discuss the machine learning system which helps remove these images before the products go online.