A Graph Positional Attention Network for Session-Based Recommendation

Author:

Dong Liyan1ORCID,Zhu Guangtong1ORCID,Wang Yuequn1ORCID,Li Yongli2,Duan Jiayao3,Sun Minghui1ORCID

Affiliation:

1. College of Computer Science and Technology, Jilin University, Changchun, China

2. School of Information Science and Technology, Northeast Normal University, Changchun, China

3. College of Software Engineering, Jilin University, Changchun, China

Funder

National Natural Science Foundation of China

Jilin Provincial Science and Technology Development Program

Central University Basic Research Fund, Jilin University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Reference37 articles.

1. Recurrent Neural Networks with Top-k Gains for Session-based Recommendations

2. Improved Recurrent Neural Networks for Session-based Recommendations

3. Session-based recommendations with recurrent neural networks;hidasi;arXiv 1511 06939,2015

4. Factorization Meets the Item Embedding

5. Sequence to sequence learning with neural networks;sutskever;Proc Adv Neural Inf Process Syst,2014

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1. SeSMR: Secure and Efficient Session-based Multimedia Recommendation in Edge Computing;ACM Transactions on Multimedia Computing, Communications, and Applications;2024-08-28

2. Attribute-Enhanced Hypergraph Neural Networks for Session-based Recommendation;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

3. Secure Position-Aware Graph Neural Networks for Session-Based Recommendation;Lecture Notes in Computer Science;2024

4. A Graph ATtention Networks Model for Session-Based Recommender Systems;2023 International Conference on Networking and Advanced Systems (ICNAS);2023-10-21

5. Attention-Enhanced Graph Neural Networks With Global Context for Session-Based Recommendation;IEEE Access;2023

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