knowledge graph embedding:主要是利用协同知识图谱的下半部分,也就是多模态知识图谱(MKG)来更新物品向量。 recommendation:主要利用用户和物品的交互信息,来更新用户向量和物品向量,最后进行打分。在讨论这些子模块之前,我们首先介绍两个关键组件:MKG Entity Encoder与MKG Attention Layer,这两个组件在两个子模块中都有...
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...
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。 •多模...
https://zheng-kai.com/paper/cikm_2020_sun.pdfzheng-kai.com/paper/cikm_2020_sun.pdf 讲解reference: Talk3-Knowledge Graph and Its Applications in Meituan Waimai_哔哩哔哩_bilibiliwww.bilibili.com/video/BV1iD4y1U7R7/?spm_id_from=333.999.0.0&vd_source=fc21edf29ec66867f2af16c5351c2c...
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...
Large-scale knowledge graphs such as Wikidata and DBpedia have become a powerful asset for semantic search and question answering. However, most of the knowledge graph construction works focus on organizing and discovering textual knowledge in a structur
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...
Multi-Modal Entity Alignment (MMEA), aiming to discover matching entity pairs on two multi-modal knowledge graphs (MMKGs), is an essential task in knowledge graph fusion. Through mining feature information of MMKGs, entities are aligned to tackle the issue that an MMKG is incapable of effective...
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 inte
感觉知识图谱和多模态结合起来,对人工要求真的高,需要的资源很多,现有工作就发发论文,这个方法研究进度还很初级。 也只有李飞飞这样的大组才能做点有意义的工作了感觉。