9 citations · 17 across the 6 of their papers we have counts for
6 papers
DeepAffinity: Long-Term Aspect Preference Prediction in eCommerce using Small Language Models
Yotam Eshel, Guy Hadad, Guy Feigenblat +3
We explore predicting eCommerce user preferences for product aspects such as brand, size, and color - a task we define as Aspect Affinity. Solving this task improves customer under…
Stageboost: Recommending Signals Based on Counterfactual Estimation
Darpan Singhal, Matan Mandelbrod, Tal Franji +3
Signals are short textual or visual snippets displayed on the eBay View-Item (VI) page, providing additional, contextual information for users about the viewed item. The aim of dis…
CoActionGraphRec: Sequential Multi-Interest Recommendations Using Co-Action Graphs
Yi Sun, Yuri M. Brovman
There are unique challenges to developing item recommender systems for e-commerce platforms like eBay due to sparse data and diverse user interests. While rich user-item interactio…
Personalized Embedding-based e-Commerce Recommendations at eBay
Tian Wang, Yuri M. Brovman, Sriganesh Madhvanath
Recommender systems are an essential component of e-commerce marketplaces, helping consumers navigate massive amounts of inventory and find what they need or love. In this paper, w…
Deep Item-based Collaborative Filtering for Sparse Implicit Feedback
Daniel A. Galron, Yuri M. Brovman, Jin Chung +2
Recommender systems are ubiquitous in the domain of e-commerce, used to improve the user experience and to market inventory, thereby increasing revenue for the site. Techniques suc…
Electric Field Effect Thermoelectric Transport in Individual Silicon and Germanium/Silicon Nanowire
Yuri M. Brovman, Joshua P. Small, Yongjie Hu +3
We have simultaneously measured conductance and thermoelectric power (TEP) of individual silicon and germanium/silicon core/shell nanowires in the field effect transistor device co…