May 13, 2024 · By aligning the representations and fusing them together, ASIF makes full use of the side information without interfering with IDs. Offline ...
ABSTRACT. Combining contextual information (i.e., side information) of items beyond IDs has become an important way to improve the perfor-.
Duration: 2:58
Posted: Mar 21, 2024
Posted: Mar 21, 2024
Apr 23, 2022 · We propose Decoupled Side Information Fusion for Sequential Recommendation (DIF-SR), which moves the side information from the input to the attention layer.
Motivation: Combining Side Information beyond lDs has become an important way to improve the performance in recommender systems. Challenges:.
Jul 7, 2022 · We propose Decoupled Side Information Fusion for Sequential Recommendation (DIF-SR), which moves the side information from the input to the attention layer.
We propose DIF-SR to effectively fuse side information for SR via moving side information from input to the attention layer.
Sequential recommender systems aim to model users' evolving interests from their historical behaviors, and hence make customized time-relevant recommendations.
Aug 20, 2024 · To this end, in this paper, we propose the Multimodal Large Language Model-enhanced Multimodal Sequential Recommendation (MLLM-MSR) model. To ...
Side information fusion for sequential recommendation (SR) aims to effectively leverage various side information to enhance the per- formance of next-item ...
Missing: Aligned | Show results with:Aligned