PEACE: Prototype lEarning Augmented transferable framework for Cross-domain rEcommendation
To help merchants/customers to provide/access a variety of services through miniapps,
online service platforms have occupied a critical position in the effective content delivery, in …
online service platforms have occupied a critical position in the effective content delivery, in …
Collaborative denoised graph contrastive learning for multi-modal recommendation
F Xu, Z Zhu, Y Fu, R Wang, P Liu - Information Sciences, 2024 - Elsevier
Graph neural networks, with their capacity to capture complex hierarchical relations, are
extensively employed in multi-modal recommendation. Previous graph-based multi-modal …
extensively employed in multi-modal recommendation. Previous graph-based multi-modal …
Behavior-Contextualized Item Preference Modeling for Multi-Behavior Recommendation
In recommender systems, multi-behavior methods have demonstrated their effectiveness in
mitigating issues like data sparsity, a common challenge in traditional single-behavior …
mitigating issues like data sparsity, a common challenge in traditional single-behavior …
Graph Transformers: A Survey
Graph transformers are a recent advancement in machine learning, offering a new class of
neural network models for graph-structured data. The synergy between transformers and …
neural network models for graph-structured data. The synergy between transformers and …
Cluster-based Graph Collaborative Filtering
Graph Convolution Networks (GCNs) have significantly succeeded in learning user and item
representations for recommendation systems. The core of their efficacy is the ability to …
representations for recommendation systems. The core of their efficacy is the ability to …
DiffMM: Multi-Modal Diffusion Model for Recommendation
Y Jiang, L Xia, W Wei, D Luo, K Lin… - arXiv preprint arXiv …, 2024 - arxiv.org
The rise of online multi-modal sharing platforms like TikTok and YouTube has enabled
personalized recommender systems to incorporate multiple modalities (such as visual …
personalized recommender systems to incorporate multiple modalities (such as visual …
SGHormer: An Energy-Saving Graph Transformer Driven by Spikes
Graph Transformers (GTs) with powerful representation learning ability make a huge
success in wide range of graph tasks. However, the costs behind outstanding performances …
success in wide range of graph tasks. However, the costs behind outstanding performances …
Enhancing Personalized Recommendations via Multimodal Cooperative Learning
C Jimenez, A Velasco, W Campbell - 2024 - researchsquare.com
Personalized recommender systems represent intelligent algorithms and decision-making
mechanisms that are meticulously crafted on the bedrock of extensive datasets. In the realm …
mechanisms that are meticulously crafted on the bedrock of extensive datasets. In the realm …
Multimodal Representation and Cross Modal Enhancement for Short Video Recommendation
S Jae-won, K Yoo-jin, J Min-seok - 2024 - researchsquare.com
The surge in short video content production on various platforms has marked the emergence
of short videos as a new and popular form of media. However, the sheer abundance and …
of short videos as a new and popular form of media. However, the sheer abundance and …
Graph Neural Networks with Rule-based Embeddings for Enhanced Recommender System
S Williams, B Smith, D Carter - 2024 - researchsquare.com
We are now entering the era of big data, transitioning from a previous era of information
scarcity to one where we face significant information overload. In this context, the challenge …
scarcity to one where we face significant information overload. In this context, the challenge …