12 citations · 25 across the 7 of their papers we have counts for
6 papers · 1 filter
BERT Goes Shopping: Comparing Distributional Models for Product Representations
Federico Bianchi, Bingqing Yu, Jacopo Tagliabue
Word embeddings (e.g., word2vec) have been applied successfully to eCommerce products through~\textit{prod2vec}. Inspired by the recent performance improvements on several NLP task…
Blending Search and Discovery: Tag-Based Query Refinement with Contextual Reinforcement Learning
Bingqing Yu, Jacopo Tagliabue
We tackle tag-based query refinement as a mobile-friendly alternative to standard facet search. We approach the inference challenge with reinforcement learning, and propose a deep…
Fantastic Embeddings and How to Align Them: Zero-Shot Inference in a Multi-Shop Scenario
Federico Bianchi, Jacopo Tagliabue, Bingqing Yu +2
This paper addresses the challenge of leveraging multiple embedding spaces for multi-shop personalization, proving that zero-shot inference is possible by transferring shopping int…
Shopping in the Multiverse: A Counterfactual Approach to In-Session Attribution
Jacopo Tagliabue, Bingqing Yu
We tackle the challenge of in-session attribution for on-site search engines in eCommerce. We phrase the problem as a causal counterfactual inference, and contrast the approach wit…
How to Grow a (Product) Tree: Personalized Category Suggestions for eCommerce Type-Ahead
Jacopo Tagliabue, Bingqing Yu, Marie Beaulieu
In an attempt to balance precision and recall in the search page, leading digital shops have been effectively nudging users into select category facets as early as in the type-ahea…
"An Image is Worth a Thousand Features": Scalable Product Representations for In-Session Type-Ahead Personalization
Bingqing Yu, Jacopo Tagliabue, Ciro Greco +1
We address the problem of personalizing query completion in a digital commerce setting, in which the bounce rate is typically high and recurring users are rare. We focus on in-sess…