Intelligent model update strategy for sequential recommendation
Modern online platforms are increasingly employing recommendation systems to address
information overload and improve user engagement. There is an evolving paradigm in this …
information overload and improve user engagement. There is an evolving paradigm in this …
A Generic Behavior-Aware Data Augmentation Framework for Sequential Recommendation
Multi-behavior sequential recommendation (MBSR), which models multi-behavior
sequentiality and heterogeneity to better learn users' multifaceted intentions has achieved …
sequentiality and heterogeneity to better learn users' multifaceted intentions has achieved …
Simplices-based higher-order enhancement graph neural network for multi-behavior recommendation
Multi-behavior recommendations effectively integrate various types of behaviors and have
been proven to enhance recommendation performance. However, existing researches …
been proven to enhance recommendation performance. However, existing researches …
Modeling multi-behavior sequence via HyperGRU contrastive network for micro-video recommendation
P Gu, H Hu, G Xu - Knowledge-Based Systems, 2024 - Elsevier
Micro-video prediction with the multi-behavior sequence remains a challenging task for
current recommendation systems. Existing approaches tend to model each individual …
current recommendation systems. Existing approaches tend to model each individual …
Revisit Targeted Model Poisoning on Federated Recommendation: Optimize via Multi-objective Transport
Federated Recommendation (FedRec) is popularly investigated in personalized
recommenders for preserving user privacy. However, due to the distributed training …
recommenders for preserving user privacy. However, due to the distributed training …
Explicit and Implicit Modeling via Dual-Path Transformer for Behavior Set-informed Sequential Recommendation
M Chen, W Pan, Z Ming - Proceedings of the 30th ACM SIGKDD …, 2024 - dl.acm.org
Sequential recommendation (SR) and multi-behavior sequential recommendation (MBSR)
both come from real-world scenarios. Compared with SR, MBSR takes into account the …
both come from real-world scenarios. Compared with SR, MBSR takes into account the …
Multi-Behavior Generative Recommendation
Multi-behavior sequential recommendation (MBSR) aims to incorporate behavior types of
interactions for better recommendations. Existing approaches focus on the next-item …
interactions for better recommendations. Existing approaches focus on the next-item …
Multi-behavior collaborative contrastive learning for sequential recommendation
Y Chen, Q Cao, X Huang, S Zou - Complex & Intelligent Systems, 2024 - Springer
Sequential recommendation (SR) predicts the user's future preferences based on the
sequence of interactions. Recently, some methods for SR have utilized contrastive learning …
sequence of interactions. Recently, some methods for SR have utilized contrastive learning …
Semantic Codebook Learning for Dynamic Recommendation Models
Dynamic sequential recommendation (DSR) can generate model parameters based on user
behavior to improve the personalization of sequential recommendation under various user …
behavior to improve the personalization of sequential recommendation under various user …
Temporal Interest Network for User Response Prediction
User response prediction is essential in industrial recommendation systems, such as online
display advertising. Among all the features in recommendation models, user behaviors are …
display advertising. Among all the features in recommendation models, user behaviors are …