Optimizkation of Health Recommendation Based on Graph Neural Network and Transformer

Xiaolong Luo

doi:10.47297/wspbdsWSP2752-630506.20250502

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Optimizkation of Health Recommendation Based on Graph Neural Network and Transformer

Volume 5, Issue 2

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Optimizkation of Health Recommendation Based on Graph Neural Network and Transformer
Optimizkation of Health Recommendation Based on Graph Neural Network and Transformer
Business School, Southwest University, Chongqing 402460, China
Vol. 5, Issue 2, Pages: 35-40(2025)
Published：18 June 2025
DOI：10.47297/wspbdsWSP2752-630506.20250502
Accepted：

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Luo Xiaolong.Optimization of Health Recommendation Based on Graph Neural Network and Transformer[J].Biomedical Data Science,2025,05(02):35-40.
DOI：

Luo Xiaolong.Optimization of Health Recommendation Based on Graph Neural Network and Transformer[J].Biomedical Data Science,2025,05(02):35-40. DOI： 10.47297/wspbdsWSP2752-630506.20250502.

摘要

Abstract

With the swift progress of intelligent health management

health recommendation systems have become a crucial part of the healthcare area. Yet

traditional recommendation systems have many issues

such as data sparsity

inaccurate feature extraction

and insufficient personalization. This paper presents an optimized health recommendation algorithm based on the Transformer model

aiming to enhance the accuracy and user experience of health recommender systems. It combines the strengths of Graph Neural Networks (GNNs) and the Transformer model. By aggregating users' historical behavior data

it can capture potential features in health information and improve recommendations. Experimental results show that the proposed algorithm outperforms traditional models in recommendation accuracy and user satisfaction.

关键词

Keywords

references

Yue W. , Wang Z. , Zhang J. , & Liu X . ( 2021 ). An overview of recommendation techniques and their applications in healthcare . IEEE/CAA Journal of Automatica Sinica , 8 ( 4 ), 701 - 717 .

Vaswani A. , Shazeer N. , Parmar N. , Uszkoreit J. , Jones L. , Gomez A. N. , ... & Polosukhin , I . 2017 . Attention is all you need. Advances in neural information processing systems, 30 .

Karypis G . ( 2001 , October ). Evaluation of item-based top-n recommendation algorithms. In Proceedings of the tenth international conference on Information and knowledge management (pp . 247 - 254 ).

W . Ying et al ., " Graph neural networks in recommender systems: A survey ," ACM Computing Surveys , vol. 55 , no. 9 , pp. 1 - 36 , 2023 .

Paul S. G. , Saha A. , Hasan M. Z. , Noori S . R . H., & Moustafa A . ( 2024 ). A systematic review of graph neural network in healthcare-based applications: Recent advances, trends, and future directions. IEEE Access, 12 , 15145 - 15170 .

Ma M. , Ren P. , Chen Z. , Ren Z. , Liang H. , Ma J. , & De Rijke M . ( 2023 ). Improving transformer-based sequential recommenders through preference editing . ACM Transactions on Information Systems , 41 ( 3 ), 1 - 24 .

Li X. , Yu X. , Liu G. , Fan X. , Ge F. , Zhao Y. , & Zheng X . ( 2024 ). Transformer-based medication recommendation with a multiple graph augmentation strategy . Expert Systems with Applications , 257 , 125091 .

Muralidharan S. , Turuvekere Sreenivas S. , Joshi R. , Chochowski M. , Patwary M. , Shoeybi M. , ... & Molchanov , P . 2024 . Compact language models via pruning and knowledge distillation. Advances in Neural Information Processing Systems, 37, 41076 - 41102 .

Hu H. , Dobbie G. , Salcic Z. , Liu M. , Zhang J. , Lyu L. , & Zhang X . ( 2023 ). Differentially private locality sensitive hashing based federated recommender system . Concurrency Computation , 35 ( 14 ), 1 - 16 .

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