Disentangled Multi-interest Representation Learning for Sequential Recommendation
Recently, much effort has been devoted to modeling users' multi-interests (aka multi-faceted
preferences) based on their behaviors, aiming to accurately capture users' complex …
preferences) based on their behaviors, aiming to accurately capture users' complex …
Triple modality fusion: Aligning visual, textual, and graph data with large language models for multi-behavior recommendations
Integrating diverse data modalities is crucial for enhancing the performance of personalized
recommendation systems. Traditional models, which often rely on singular data sources …
recommendation systems. Traditional models, which often rely on singular data sources …
Knowledge Graph Context-Enhanced Diversified Recommendation
The field of Recommender Systems (RecSys) has been extensively studied to enhance
accuracy by leveraging users' historical interactions. Nonetheless, this persistent pursuit of …
accuracy by leveraging users' historical interactions. Nonetheless, this persistent pursuit of …
Collaborative Alignment for Recommendation
Traditional recommender systems have primarily relied on identity representations (IDs) to
model users and items. Recently, the integration of pre-trained language models (PLMs) has …
model users and items. Recently, the integration of pre-trained language models (PLMs) has …
Disentangled Self-Attention with Auto-Regressive Contrastive Learning for Neural Group Recommendation
Group recommender systems aim to provide recommendations to a group of users as a
whole rather than to individual users. Nonetheless, prevailing methodologies predominantly …
whole rather than to individual users. Nonetheless, prevailing methodologies predominantly …
A Collaborative Ensemble Framework for CTR Prediction
Recent advances in foundation models have established scaling laws that enable the
development of larger models to achieve enhanced performance, motivating extensive …
development of larger models to achieve enhanced performance, motivating extensive …
Multi-task Recommendation in Marketplace via Knowledge Attentive Graph Convolutional Network with Adaptive Contrastive Learning
Marketplaces with multiple sellers have progressively evolved into viable business models
in many web applications. Within this sphere, a marketplace recommendation model …
in many web applications. Within this sphere, a marketplace recommendation model …