SiReN: Sign-Aware Recommendation Using Graph Neural Networks
Author:
Affiliation:
1. School of Mathematics and Computing (Computational Science and Engineering), Yonsei University, Seoul 03722, South Korea.
2. Department of Computer Science and Engineering, Chungnam National University, Daejeon 34134, South Korea.
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software
Link
http://xplorestaging.ieee.org/ielx7/5962385/6104215/09781816.pdf?arnumber=9781816
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1. An unclosed structures-preserving embedding model for signed networks;Neurocomputing;2024-04
2. MONET: Modality-Embracing Graph Convolutional Network and Target-Aware Attention for Multimedia Recommendation;Proceedings of the 17th ACM International Conference on Web Search and Data Mining;2024-03-04
3. Learning from Negative User Feedback and Measuring Responsiveness for Sequential Recommenders;Proceedings of the 17th ACM Conference on Recommender Systems;2023-09-14
4. Understanding and Modeling Passive-Negative Feedback for Short-video Sequential Recommendation;Proceedings of the 17th ACM Conference on Recommender Systems;2023-09-14
5. Negative Can Be Positive: Signed Graph Neural Networks for Recommendation;Information Processing & Management;2023-07
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