LSTM-UBI: a user behavior inertia based recommendation method-Reference-Cited by-同舟云学术

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LSTM-UBI: a user behavior inertia based recommendation method

Published:2024-01-31 Issue:27 Volume:83 Page:69227-69248
ISSN:1573-7721
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Zhang Kaiqi,Chu Dianhui,Tu Zhiying,Liu Xiaolin,Zhang Bolin

Funder

National Key Research and Development Project of China

Shandong Province Key Research and Development Project

Natural Science Foundation of Shandong Province

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11042-024-18256-2.pdf

Reference64 articles.

1. Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9(8):1735–1780

2. Wang L, Zhang C, Chen Q (2018) A communication strategy of proactive nodes based on loop theorem in wireless sensor networks. In: Proceedings of the 2018 ninth international conference on intelligent control and information processing (ICICIP), pp 1296–1305

3. Zhu Y (2017) What to do next: modeling user behaviors by time-lstm. In: Proceedings of the twenty-sixth international joint conference on artificial intelligence, IJCAI, pp 3602–3608

4. Fu H, Li J, Chen J (2018) Sequence-based recommendation with bidirectional lstm network. In: Advances in multimedia information processing-PCM, pp 428–438

5. Zhou Y, Ushiama T (2019) Lstm-based recommendation approach for interaction records. In: Proceedings of the 13th international conference on ubiquitous information management and communication IMCOM), pp 950–962

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