most citedCF-KAN: Kolmogorov-Arnold Network-based Collaborative Filtering to Mitigate Catastrophic Forgetting in Recommender Systems

3 citations · 4 across the 3 of their papers we have counts for

collaborators

3 papers

cs.IR2024★ 3 cited

CF-KAN: Kolmogorov-Arnold Network-based Collaborative Filtering to Mitigate Catastrophic Forgetting in Recommender Systems

Jin-Duk Park, Kyung-Min Kim, Won-Yong Shin

Collaborative filtering (CF) remains essential in recommender systems, leveraging user--item interactions to provide personalized recommendations. Meanwhile, a number of CF techniq…

cs.LG2024

LAMP: Learnable Meta-Path Guided Adversarial Contrastive Learning for Heterogeneous Graphs

Siqing Li, Jin-Duk Park, Wei Huang +3

Heterogeneous graph neural networks (HGNNs) have significantly propelled the information retrieval (IR) field. Still, the effectiveness of HGNNs heavily relies on high-quality labe…

cs.AI2022★ 1 cited

Two-Stage Deep Anomaly Detection with Heterogeneous Time Series Data

Kyeong-Joong Jeong, Jin-Duk Park, Kyusoon Hwang +2

We introduce a data-driven anomaly detection framework using a manufacturing dataset collected from a factory assembly line. Given heterogeneous time series data consisting of oper…