923 citations · 1.2k across the 21 of their papers we have counts for
6 papers · 1 filter
Bilateral Self-unbiased Learning from Biased Implicit Feedback
Jae-woong Lee, Seongmin Park, Joonseok Lee +1
Implicit feedback has been widely used to build commercial recommender systems. Because observed feedback represents users' click logs, there is a semantic gap between true relevan…
S-Walk: Accurate and Scalable Session-based Recommendationwith Random Walks
Minjin Choi, Jinhong Kim, Joonsek Lee +2
Session-based recommendation (SR) predicts the next items from a sequence of previous items consumed by an anonymous user. Most existing SR models focus only on modeling intra-sess…
Local Collaborative Autoencoders
Minjin Choi, Yoonki Jeong, Joonseok Lee +1
Top-N recommendation is a challenging problem because complex and sparse user-item interactions should be adequately addressed to achieve high-quality recommendation results. The l…
Session-aware Linear Item-Item Models for Session-based Recommendation
Minjin Choi, jinhong Kim, Joonseok Lee +2
Session-based recommendation aims at predicting the next item given a sequence of previous items consumed in the session, e.g., on e-commerce or multimedia streaming services. Spec…
Personalized Academic Research Paper Recommendation System
Joonseok Lee, Kisung Lee, Jennifer G. Kim
A huge number of academic papers are coming out from a lot of conferences and journals these days. In these circumstances, most researchers rely on key-based search or browsing thr…
A Comparative Study of Collaborative Filtering Algorithms
Joonseok Lee, Mingxuan Sun, Guy Lebanon
Collaborative filtering is a rapidly advancing research area. Every year several new techniques are proposed and yet it is not clear which of the techniques work best and under wha…