1 citations · 1 across the 9 of their papers we have counts for
4 papers · 1 filter
MURAL: Multimodal Uncertainty-aware Recommendation via Adaptive edge Learning
Ahmad Mousavi, Majid Alikhani, Yeon-Chang Lee +2
Multimodal Graph Neural Networks have become standard for recommendation by augmenting sparse interaction data with content features. Yet current architectures face two bottlenecks…
Anchored Alignment: Preventing Positional Collapse in Multimodal Recommender Systems
Yonghun Jeong, David Yoon Suk Kang, Yeon-Chang Lee
Multimodal recommender systems (MMRS) leverage images, text, and interaction signals to enrich item representations. However, recent alignment based MMRSs that enforce a unified em…
E-MMKGR: A Unified Multimodal Knowledge Graph Framework for E-commerce Applications
Jiwoo Kang, Yeon-Chang Lee
Multimodal recommender systems (MMRSs) enhance collaborative filtering by leveraging item-side modalities, but their reliance on a fixed set of modalities and task-specific objecti…
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…