7 papers
EGRA:Toward Enhanced Behavior Graphs and Representation Alignment for Multimodal Recommendation
Xiaoxiong Zhang, Xin Zhou, Zhiwei Zeng +2
MultiModal Recommendation (MMR) systems have emerged as a promising solution for improving recommendation quality by leveraging rich item-side modality information, prompting a sur…
Low-Dimensional Federated Knowledge Graph Embedding via Knowledge Distillation
Xiaoxiong Zhang, Zhiwei Zeng, Xin Zhou +1
Federated Knowledge Graph Embedding (FKGE) aims to facilitate collaborative learning of entity and relation embeddings from distributed Knowledge Graphs (KGs) across multiple clien…
Semantic Item Graph Enhancement for Multimodal Recommendation
Xiaoxiong Zhang, Xin Zhou, Zhiwei Zeng +2
Multimodal recommendation systems have attracted increasing attention for their improved performance by leveraging items' multimodal information. Prior methods often build modality…
Learning Item Representations Directly from Multimodal Features for Effective Recommendation
Xin Zhou, Xiaoxiong Zhang, Dusit Niyato +1
Conventional multimodal recommender systems predominantly leverage Bayesian Personalized Ranking (BPR) optimization to learn item representations by amalgamating item identity (ID)…
Advancing Sustainability via Recommender Systems: A Survey
Xin Zhou, Lei Zhang, Honglei Zhang +4
Human behavioral patterns and consumption paradigms have emerged as pivotal determinants in environmental degradation and climate change, with quotidian decisions pertaining to tra…
Communication-Efficient Federated Knowledge Graph Embedding with Entity-Wise Top-K Sparsification
Xiaoxiong Zhang, Zhiwei Zeng, Xin Zhou +2
Federated Knowledge Graphs Embedding learning (FKGE) encounters challenges in communication efficiency stemming from the considerable size of parameters and extensive communication…