Three graph types ( static, temporal, multi-modal KGs) Static knowledge graph (KG) : is defined as SKG = {E, R, F }, where E, R, and F represent the sets ofentities, relations, and facts. The fact is in a triplet format(e_h, r, e_t)∈ F, wheree_h, e_t ∈ E, andr ...
论文阅读 TEMPORAL GRAPH NETWORKS FOR DEEP LEARNING ON DYNAMIC GRAPHS link: https://scholar.google.com.hk/scholar_url?url=https://arxiv.org/pdf/2006.10637.pdf%3Fref%3Dhttps://githubhelp.com&hl=zh-TW&sa=X&ei=oVakYtvtIo74yASQ1Jj4AQ&… 打不过野我...发表于动态图嵌入 再...
Entity Alignment (EA) is a crucial task in knowledge fusion, which aims to link entities with the same real-world identity from different Knowledge Graphs (KGs). Existing methods have achieved satisfactory performance, however, they mainly focus on single modal KG, which is difficult to be effec...
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
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 appli...
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...
Code Issues Pull requests Actions Projects Security Insights Additional navigation options main 1Branch0Tags 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 Gr...
Fig. 33.The pipeline of the multi-modal spatiotemporal architecture for deep depression recognition. The approach first inputs spectrogram/video segments into the Spatio-Temporal Attention (STA) network and then uses the features of the last fully connected layers for the Audio Segment-Level Feature...
【论文笔记】RippleNet : 知识图谱+用户偏好传播的推荐系统 notanumbb 开放知识图谱构建调研 一、OpenIE stanford-openie支持最新的CoreNLP库4.5.3(截至2023-03-10)。 开放信息提取(Open IE)是指从纯文本中提取结构化关系三元组,这样就不需要预先指定这些关系的模式。例如,巴拉克奥… Malwarehunter 个人开源知识图谱...
ProteinKG65主要致力于提供一个专业的蛋白质知识图谱,将基因本体论的知识带入蛋白质功能和结构预测。最新版本包含614099个实体,5620437个三元组(包含5510437个蛋白质-GO三元组和110000个GO-GO三元组)作者还用一个原型来说明ProteinKG65潜在应用。该数据集可以在https://w3id.org/proteinkg65进行下载。