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Track 3

Data Science for e-Commerce

sponsored by "StuccoMedia"

organized by Shay Bushinsky and Shmuel Ur

Background:

StuccoMedia's unique technology makes eCommerce smart and friendly by using a cloud based platform which fully automates the online advertising process. Our engine cleverly selects the products to advertise, and generates unique campaigns for individual products. Automatically and without interference our engine then dictates the absolute best placement for each ad. At the heart of our system lies the ability to track and learn consumers' distinctive behavior throughout their unique journey towards the purchase of goods or services.

Examples of projects:

  1. Click Rate prediction task: Given a historical data set of products and users that clicked / purchased them - predict the click rate of any given product.

  2. Price comparison utility: Given a list of products from different web sources which are described both verbally and visually but not necessarily in the same way, classify which products are identical and thus comparable.

  3. Product catalog unifier: Given two or several different sets of products and  their catalogs (originating from different web stores with considerable product intersection) - find  an optimal way to categorize all the products under a single unified catalog.

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