5 citations · 13 across the 7 of their papers we have counts for
3 papers · 1 filter
SVD-AE: Simple Autoencoders for Collaborative Filtering
Seoyoung Hong, Jeongwhan Choi, Yeon-Chang Lee +2
Collaborative filtering (CF) methods for recommendation systems have been extensively researched, ranging from matrix factorization and autoencoder-based to graph filtering-based m…
TimeKit: A Time-series Forecasting-based Upgrade Kit for Collaborative Filtering
Seoyoung Hong, Minju Jo, Seungji Kook +4
Recommender systems are a long-standing research problem in data mining and machine learning. They are incremental in nature, as new user-item interaction logs arrive. In real-worl…
Blurring-Sharpening Process Models for Collaborative Filtering
Jeongwhan Choi, Seoyoung Hong, Noseong Park +1
Collaborative filtering is one of the most fundamental topics for recommender systems. Various methods have been proposed for collaborative filtering, ranging from matrix factoriza…