Multi-Head Attention and Knowledge Graph Based Dual Target Graph Collaborative Filtering Network-Reference-Cited by-同舟云学术

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Multi-Head Attention and Knowledge Graph Based Dual Target Graph Collaborative Filtering Network

Published:2023-05-04 Issue:7 Volume:55 Page:9155-9177
ISSN:1370-4621
Container-title:Neural Processing Letters
language:en
Short-container-title:Neural Process Lett

Author:

Yu Xu,Peng Qinglong,Jiang Feng,Du Junwei,Liang Hongtao,Liu Jinhuan

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shandong Province

the Fundamental Research Funds for the Central Universities, JLU

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Networks and Communications,General Neuroscience,Software

Link

https://link.springer.com/content/pdf/10.1007/s11063-023-11197-1.pdf

Reference37 articles.

1. He X, Deng K, Wang X, et al (2020) Lightgcn: simplifying and powering graph convolution network for recommendation. In: the 43rd international ACM SIGIR conference on research and development in information retrieval, pp 639–648

2. Zhu F, Wang Y, Chen C, et al (2020) A graphical and attentional framework for dual-target cross-domain recommendation. In: the 29th international joint conference on artificial intelligence and the 17th Pacific rim international conference on artificial intelligence, pp 3001–3008

3. Yu X, Peng Q, Xu L et al (2021) A selective ensemble learning based two-sided cross-domain collaborative filtering algorithm. Inf Process Manag 58(6):102691

4. Fu M, Qu H, Yi Z et al (2018) A novel deep learning-based collaborative filtering model for recommendation system. IEEE Trans Cybern 49(3):1084–1096

5. He X, Liao L, Zhang H, et al (2017) Neural collaborative filtering. In: the 26th international conference on World Wide Web, pp 173–182

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