5.1Multi-modal Knowledge Graph Embedding Figure 4中呈现的encoder的具体信息是: 然后propagation layer的使用方式:知识图谱的结构学习是使用TransE模型(h+r≈t),然后这里的aggregation方式是不aggregation邻居=>而是aggregate多模态实体来传播更新特征。 这里的propagation是在于传播三元组的embedding,公式如下: 这里的pai就...
本文提出了一种名为Multi-modal Knowledge Graph Attention Network (MKGAT)的模型。 模型的输入输出分别是: 输入:数据集的协同知识图谱。 输出:用户向量e∗ueu∗和物品向量e∗iei∗。最终,模型预测的用户uu对物品ii的感兴趣程度^y(u,i)y^(u,i)由公式^y(u,i)=e∗ Tue∗iy^(u,i)=eu∗ Te...
(4)长期以来,转导推理模型不断出现,对学术研究和工业应用产生了巨大影响。 Temporal Knowledge Graph. Temporal knowledge graph (KG) is defined as a sequence of static KGs at different timestampsTKG=\{SKG_1, SKG_2, SKG_3, ··· , SKG_t\}. The KG snapshot at timestamp t is defined asSK...
在讨论子模块之前,我们首先介绍了两个关键组件:多模态知识图谱实体编码器(multi-modal knowledge graph entity encoder)和多模态知识图谱注意层(multi-modal knowledge graph attention layer),它们是KG嵌入模块和推荐模块的基本构建块。 •多模态知识图谱实体编码器,使用不同的编码器嵌入每种特定的数据类型。
Entity alignment plays an essential role in the knowledge graph (KG) integration. Though large efforts have been made on exploring the association of relational embeddings between different knowledge graphs, they may fail to effectively describe and integrate the multi-modal knowledge in the real ...
Projects Security Insights Additional navigation options main BranchesTags Code README MIT license SNAG In this work, we introduce aUnified Multi-Modal Knowledge Graph (MMKG) Representation Frameworkthat incorporates tailored training objectives for Multi-modal Knowledge Graph Completion (MKGC) and Multi-...
Novel data sets for benchmarking knowledge graph completion approaches, therefore, are important contributions to the community. This is especially true since one method performing well on one data set might perform poorly on others [23]. With this paper we introduce Mmkg (Multi-Modal Knowledge Gr...
论文题目:Beyond Entities: A Large-Scale Multi-Modal Knowledge Graph with Triplet Fact Grounding 作者:Jingping Liu, Mingchuan Zhang, Weichen Li , Chao Wang, Shuang Li, Haiyun Jiang, Sihang Jiang, Y…
Entity Alignment Knowledge Graphs Multi-modal Entity Alignment Multi-modal Knowledge Graph Datasets Edit MMKG Results from the Paper Edit Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers. Methods...
has not yet received much attention compared to those applications. We introduce RECipe as a multi-purpose recipe recommendation framework with a multi-modal knowledge graph (MMKG) backbone. The motivation behind RECipe is to go beyond (deep) neural collaborative filtering (NCF) by recommending recip...