6 citations · 9 across the 5 of their papers we have counts for
6 papers · 1 filter
Mitigating Frequency Bias in Next-Basket Recommendation via Deconfounders
Xiaohan Li, Zheng Liu, Luyi Ma +4
Recent studies on Next-basket Recommendation (NBR) have achieved much progress by leveraging Personalized Item Frequency (PIF) as one of the main features, which measures the frequ…
Causal Structure Learning with Recommendation System
Shuyuan Xu, Da Xu, Evren Korpeoglu +4
A fundamental challenge of recommendation systems (RS) is understanding the causal dynamics underlying users' decision making. Most existing literature addresses this problem by us…
A Real-Time Whole Page Personalization Framework for E-Commerce
Aditya Mantha, Anirudha Sundaresan, Shashank Kedia +6
E-commerce platforms consistently aim to provide personalized recommendations to drive user engagement, enhance overall user experience, and improve business metrics. Most e-commer…
Basket Recommendation with Multi-Intent Translation Graph Neural Network
Zhiwei Liu, Xiaohan Li, Ziwei Fan +3
The problem of basket recommendation~(BR) is to recommend a ranking list of items to the current basket. Existing methods solve this problem by assuming the items within the same b…
BasConv: Aggregating Heterogeneous Interactions for Basket Recommendation with Graph Convolutional Neural Network
Zhiwei Liu, Mengting Wan, Stephen Guo +2
Within-basket recommendation reduces the exploration time of users, where the user's intention of the basket matters. The intent of a shopping basket can be retrieved from both use…
A Large-Scale Deep Architecture for Personalized Grocery Basket Recommendations
Aditya Mantha, Yokila Arora, Shubham Gupta +4
With growing consumer adoption of online grocery shopping through platforms such as Amazon Fresh, Instacart, and Walmart Grocery, there is a pressing business need to provide relev…