no code implementations • 20 Oct 2023 • Bowen Hao, Chaoqun Yang, Lei Guo, Junliang Yu, Hongzhi Yin
By unifying pre-training and recommendation tasks as a common motif-based similarity learning task and integrating adaptable prompt parameters to guide the model in downstream recommendation tasks, MOP excels in transferring domain knowledge effectively.
no code implementations • 4 Dec 2021 • Bowen Hao, Hongzhi Yin, Jing Zhang, Cuiping Li, Hong Chen
In terms of the pretext task, in addition to considering the intra-correlations of users and items by the embedding reconstruction task, we add embedding contrastive learning task to capture inter-correlations of users and items.
no code implementations • 4 Dec 2021 • Bowen Hao, Hongzhi Yin, Cuiping Li, Hong Chen
As each occasional group has extremely sparse interactions with items, traditional group recommendation methods can not learn high-quality group representations.
1 code implementation • 28 Dec 2020 • Bowen Hao, Jing Zhang, Cuiping Li, Hong Chen, Hongzhi Yin
On the one hand, the framework enables training multiple supervised ranking models upon the pseudo labels produced by multiple unsupervised ranking models.
1 code implementation • 13 Dec 2020 • Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li, Hong Chen
Cold-start problem is a fundamental challenge for recommendation tasks.