12 citations · 18 across the 4 of their papers we have counts for
5 papers · 1 filter
"Does it come in black?" CLIP-like models are zero-shot recommenders
Patrick John Chia, Jacopo Tagliabue, Federico Bianchi +2
Product discovery is a crucial component for online shopping. However, item-to-item recommendations today do not allow users to explore changes along selected dimensions: given a q…
SIGIR 2021 E-Commerce Workshop Data Challenge
Jacopo Tagliabue, Ciro Greco, Jean-Francis Roy +4
The 2021 SIGIR workshop on eCommerce is hosting the Coveo Data Challenge for "In-session prediction for purchase intent and recommendations". The challenge addresses the growing ne…
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…
"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…
Prediction is very hard, especially about conversion. Predicting user purchases from clickstream data in fashion e-commerce
Luca Bigon, Giovanni Cassani, Ciro Greco +4
Knowing if a user is a buyer vs window shopper solely based on clickstream data is of crucial importance for ecommerce platforms seeking to implement real-time accurate NBA (next b…