Integrating Behavioral Dependencies into Multi-task Learning for Personalized Recommendations
The introduction of multiple types of behavioral data alleviates the data sparsity and cold-start problems of collaborative filtering algorithms, which is widely studied and applied in the field of recommendations. Although great progress has been made in the current research on multi-behavior recom...
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Format: | Article |
Language: | zho |
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Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
2024-01-01
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Series: | Jisuanji kexue yu tansuo |
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Online Access: | http://fcst.ceaj.org/fileup/1673-9418/PDF/2208098.pdf |