其中第二项是采用的贝叶斯个性化排名 (BPR) 损失,eu代表用户嵌入,ei代表正的项目嵌入,yui代表真实值,Ds={(u,i,j)|(u,i)属于R+,(u,j)属于R-}是训练集数据,R+代表观察到的交互,R-代表未观察到的交互,σ代表sigmoid操作,因为 Lssl 没有引入其他参数,Θ是 BPR 损失中的模型参数集,而λ1 和λ2 分别...
论文题目:Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Survey论文链接:http://arxiv.org/abs/2402.05391 引言 本综述深入分析了2020至2023年间超过300篇文献,聚焦于两个主要方向:一是知识图谱驱动的多模态学习(KG4MM),探讨知识图谱如何支持多模态任务;二是多模态知识图谱(MM4KG),研究如何将知识图谱...
To address this, we propose a Multi-modal GraphNet Learning-Based Feature Extraction approach. Our method integrates multi-modal information from both spatial and temporal domains to enhance saliency detection accuracy. By leveraging GraphNet, we effectively model the intricate relat...
To this end, we propose an end-to-end Multi-modal Graph Learning framework (MMGL) for disease prediction with multi-modality. To effectively exploit the rich information across multi-modality associated with the disease, modality-aware representation learning is proposed to aggregate the features of...
Multi-modal Graph learning for Disease Prediction (IEEE Trans. on Medical imaging, TMI2022) - SsGood/MMGL
Traditional knowledge graphs (KG) representation learning focuses on the link information between entities, and the effectiveness of learning is influenced by the complexity of KGs. Considering a multi-modal knowledge graph (MKG), due to the introduction of considerable other modal information(such as...
基于图神经网络的消息传递思想,我们设计了一个多模态图卷积网络(Multi-modal Graph Convolution Network,MMGCN)框架,该框架可以生成用户和微视频特定模态的表征,以更好地捕捉用户的偏好。具体地说,我们在每个模态上构造一个用户-项目二分图(bipartite graph),并用其邻接节点的拓扑结构和特征来丰富每个节点的表征。通过...
We believe this data set has the potential to facilitate the development of novel multi-modal learning approaches for knowledge graphs. We validate the utility of Mmkg in the sameAs link prediction task with an extensive set of experiments. These experiments show that the task at hand benefits ...
Wei Y., Wang X., Nie L., He X., Hong R. and Chua T. MMGCN: Multi-modal graph convolution network for personalized recommendation of micro-video. MM, 2019. 概 推荐领域里比较早的多模态方法. 符号说明 UU, user set; II, item set; ...
Inspired by synaesthesia, multi-modal cognitive computing endows machines with multi-sensory capabilities and has become the key to general artificial intelligence. With the explosion of multi-modal data such as image, video, text, and audio, a large number of methods have been developed to ...