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Wednesday, October 17 • 11:15am - 11:55am
Image-Based E-Commerce Product Discovery: A Deep Learning Case Study

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To further improve discoverability of Macy’s product catalog online we introduced an easy shopping experience for finding products which are hard to describe using text-based search. The feature allows customers to use an existing product on the website and find all matching products which are similar to the original product based on its image. Deep-learning algorithms are applied to product images to provide an experience. To enhance it further a new component is developed to evaluate the signals other that image similarity, such as product attribute similarity, customer’s shopping preferences, business rules etc. Current talk gives some insights on implementation and overall feature architecture.

avatar for Peter Gazaryan

Peter Gazaryan

Senior Architect, Search & Browse, Macy's
Peter joined Macy’s in 2013 as a Technical Solution Manager. In his current role Peter is leading the projects in integrating the different software systems providing search and browse functionality to macys.com customers. Peter received his Master degree in the Electrical Engineering from South-Russian State Technical University... Read More →
avatar for Denis Kamotsky

Denis Kamotsky

Principal Engineer, Macy's
Denis Kamotsky joined Macy’s in 2001 at the time of the company's first Java-based web site launch and thereafter has been actively contributing in multiple areas of macys.com development as an engineer and a solution architect. Since early 2011 Denis has been leading a team responsible... Read More →

Wednesday October 17, 2018 11:15am - 11:55am EDT
Salon 6&7