3 papers
cs.IR2026
AlphaFree: Recommendation Free from Users, IDs, and GNNs
Minseo Jeon, Junwoo Jung, Daewon Gwak +1
Can we design effective recommender systems free from users, IDs, and GNNs? Recommender systems are central to personalized content delivery across domains, with top-K item recomme…
cs.IR2025
Personalized Ranking on Cascading Behavior Graphs for Accurate Multi-Behavior Recommendation
Geonwoo Ko, Minseo Jeon, Jinhong Jung
Multi-behavior recommendation predicts items a user may purchase by analyzing diverse behaviors like viewing, adding to a cart, and purchasing. Existing methods fall into two categ…
cs.LG2024
Effective and Lightweight Representation Learning for Link Sign Prediction in Signed Bipartite Graphs
Gyeongmin Gu, Minseo Jeon, Hyun-Je Song +1
How can we effectively and efficiently learn node representations in signed bipartite graphs? A signed bipartite graph is a graph consisting of two nodes sets where nodes of differ…