Blog Author: Chen Xue

How eBay Created a Language Model With Three Billion Item Titles

By leveraging deep learning techniques to compare the titles of product listings, we greatly improved the relevance of our recommended items on eBay’s View Item page.

By: Chen Xue, Jesse Lute, Dan Schonfeld, Guoping Han and Leonard Dahlmann

Advertising in Engineering

Multi-Objective Ranking for Promoted Auction Items

Determining which promoted auction items to display in a merchandising placement is a multi-sided customer challenge that presents opportunities to both surface amazing auction inventory to buyers and help sellers boost visibility on their auction listings.

By: Ishaan Arora, Chen Xue, Jesse Lute and Dan Schonfeld

Advertising in Engineering

Multi-Relevance Ranking Model for Similar Item Recommendation

Buyers reveal a whole range of behaviors and interests when they browse our pages, so we decided to incorporate these additional purchase intent signals into our machine learning model to improve the relevance of our recommended items.

By: Chen Xue, Rachel Vishnepolsky and Zhen Ge

Advertising in Engineering

Improving Shopping Recommendations for Customers Through eBay’s Relevance Cascade Model

Under the new machine learning model, buyers are recommended items that are more aligned to their shopping interests on eBay.

By: Chen Xue, Applied Researcher

Chen Xue is an applied researcher and the tech lead of Merch Ads Research and Training Team (MADRAT) at eBay. Her work focuses specifically on Sponsored Similar Item Recommendation to help buyers find relevant items and drive revenue for eBay. She worked as a data engineer at Spotify for 3 years before joining eBay in 2019. She obtained her MS in Energy Resources Engineering from Stanford University, and BS in Statistics from Sun Yat-Sen University in China.

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