Search Results for author: Eunkyu Oh

Found 3 papers, 0 papers with code

TempGNN: Temporal Graph Neural Networks for Dynamic Session-Based Recommendations

no code implementations20 Oct 2023 Eunkyu Oh, Taehun Kim

Session-based recommendations which predict the next action by understanding a user's interaction behavior with items within a relatively short ongoing session have recently gained increasing popularity.

Session-Based Recommendations

STING: Self-attention based Time-series Imputation Networks using GAN

no code implementations22 Sep 2022 Eunkyu Oh, Taehun Kim, Yunhu Ji, Sushil Khyalia

Although recent works based on deep neural networks have shown remarkable results, they still have a limitation to capture the complex generation process of the multivariate time series.

Imputation Time Series +1

SR-GCL: Session-Based Recommendation with Global Context Enhanced Augmentation in Contrastive Learning

no code implementations22 Sep 2022 Eunkyu Oh, Taehun Kim, Minsoo Kim, Yunhu Ji, Sushil Khyalia

As a crucial component of contrastive learning, we propose two global context enhanced data augmentation methods while maintaining the semantics of the original session.

Contrastive Learning Data Augmentation +1

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