Research on Graph Network Recommendation Algorithm Based on Random Walk and Convolutional Neural Network-Reference-Cited by-同舟云学术

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Research on Graph Network Recommendation Algorithm Based on Random Walk and Convolutional Neural Network

Published:2021-12-05 Issue: Volume: Page:
ISSN:
Container-title:2021 International Conference on High Performance Big Data and Intelligent Systems (HPBD&IS)
language:
Short-container-title:

Author:

Huang Meng

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9658414/9658338/09658461.pdf?arnumber=9658461

Reference40 articles.

1. Personalized entity recommendation

2. Factorization Machines

3. Convolutional Matrix Factorization for Document Context-Aware Recommendation

4. A Personalized QoS Prediction Method for Web Services via Blockchain-Based Matrix Factorization

5. Dynamic Attention Deep Model for ArticleRecommendation by Learning Human Editor ’ s Demonstration[C];wang;Proceedings of the 23rd SIGKDD International Conference on Knowledge and Data Mining,2017

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1. Semi-supervised heterogeneous graph contrastive learning with label-guided;Applied Intelligence;2024-08-03

2. Auto-encoder and Graph Neural Networks-Based Hybrid Model for Link Prediction on Complex Network;Intelligent Computing and Networking;2023

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