A deep low-rank semantic factorization method for micro-video multi-label classification-Reference-Cited by-同舟云学术

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A deep low-rank semantic factorization method for micro-video multi-label classification

Published:2024-08 Issue:4 Volume:30 Page:
ISSN:0942-4962
Container-title:Multimedia Systems
language:en
Short-container-title:Multimedia Systems

Author:

Fan Fugui,Su Yuting,Liu Yun,Jing Peiguang,Qu Kaihua

Funder

National Natural Science Foundation of China

Natural Science Foundation of Liaoning Province

Shenyang Science and Technology Plan Project

Research Fund of Guangxi Key Lab of Multi-source Information Mining and Security

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00530-024-01428-3.pdf

Reference53 articles.

1. He, Y., Wu, G., Cai, D., Hu, X.: Cross-view sample-enriched graph contrastive learning network for personalized micro-video recommendation. In: Proceedings of the ACM International Conference on Multimedia Retrieval, pp. 48–56 (2023)

2. Shang, Y., Gao, C., Chen, J., Jin, D., Wang, M., Li, Y.: Learning fine-grained user interests for micro-video recommendation. In: Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 433–442 (2023)

3. Lu, W., Lin, J., Jing, P., Su, Y.: A multimodal aggregation network with serial self-attention mechanism for micro-video multi-label classification. IEEE Signal Process. Lett. 30, 60–64 (2023)

4. Jing, P., Cui, K., Zhang, J., Li, Y., Su, Y.: Multimodal high-order relationship inference network for fashion compatibility modeling in internet of multimedia things. IEEE Internet Things J. 11(1), 353–365 (2024)

5. Liu, M., Nie, L., Wang, X., Tian, Q., Chen, B.: Online data organizer: micro-video categorization by structure-guided multimodal dictionary learning. IEEE Trans. Image Process. 28(3), 1235–1247 (2018)

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