SR-HetGNN: session-based recommendation with heterogeneous graph neural network-Reference-Cited by-同舟云学术

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SR-HetGNN: session-based recommendation with heterogeneous graph neural network

Published:2023-09-25 Issue:2 Volume:66 Page:1111-1134
ISSN:0219-1377
Container-title:Knowledge and Information Systems
language:en
Short-container-title:Knowl Inf Syst

Author:

Chen Jinpeng,Li Haiyang,Zhang Xudong,Zhang Fan,Wang Senzhang,Wei Kaimin,Ji Jiaqi

Funder

Open Projects of the Technology Innovation Center of Cultural Tourism Big Data of Hebei Province

Zhejiang Lab Open Research Project

the National Natural Science Foundation of China

National Key R&D Program of China

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Hardware and Architecture,Human-Computer Interaction,Information Systems,Software

Link

https://link.springer.com/content/pdf/10.1007/s10115-023-01986-4.pdf

Reference37 articles.

1. Wang S, Cao L, Wang Y (2019) A survey on session-based recommender systems. arXiv preprint arXiv:1902.04864

2. Wu S, Tang Y, Zhu Y, Wang L, Xie X, Tan T (2019) Session-based recommendation with graph neural networks. In: Proceedings of the AAAI conference on artificial intelligence, vol 33, pp 346–353

3. Sun Y, Han J, Yan X, Yu PS, Wu T (2011) Pathsim: meta path-based top-k similarity search in heterogeneous information networks. Proc VLDB Endow 4(11):992–1003

4. Zhang C, Song D, Huang C, Swami A, Chawla NV (2019) Heterogeneous graph neural network. In: Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery and data mining, pp 793–803

5. Barajas JM, Li X (2005) Collaborative filtering on data streams. In: Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery and data mining, pp 429–436

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