AutoAssign+: Automatic Shared Embedding Assignment in streaming recommendation-Reference-Cited by-同舟云学术

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AutoAssign+: Automatic Shared Embedding Assignment in streaming recommendation

Published:2023-08-13 Issue:1 Volume:66 Page:89-113
ISSN:0219-1377
Container-title:Knowledge and Information Systems
language:en
Short-container-title:Knowl Inf Syst

Author:

Liu Ziru,Chen Kecheng,Song Fengyi,Chen Bo,Zhao Xiangyu,Guo Huifeng,Tang Ruiming

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/s10115-023-01951-1.pdf

Reference56 articles.

1. An M, Wu F, Wu C, Zhang K, Liu Z, Xie X (2019) Neural news recommendation with long-and short-term user representations. In: ACL, pp. 336–345

2. Ren K, Zhang W, Rong Y, Zhang H, Yu Y, Wang J (2016) User response learning for directly optimizing campaign performance in display advertising. In: CIKM, pp. 679–688

3. Guo L, Yin H, Wang Q, Chen T, Zhou A, Quoc Viet Hung N (2019) Streaming session-based recommendation. In: KDD, pp. 1569–1577

4. He B, He X, Zhang Y, Tang R, Ma C (2023) Dynamically expandable graph convolution for streaming recommendation. In: Proceedings of the ACM web conference 2023, Austin, TX, USA. Association for Computing Machinery, New York, pp 1457–1467

5. Guo H, Chen B, Tang R, Zhang W, Li Z, He X (2021) An embedding learning framework for numerical features in ctr prediction. In: KDD

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