2021.03.09: 修正关于引入逆三元组的影响. 2021.04.18: 更新一篇更早的类似论文GAKE. LightCAKE: A Lightweight Framework for Context-Aware Knowledge

本文前置知识: 图结构基础知识(数据结构相关内容, 自行查阅). 2021.04.06: 更新GraphSAGE的理解. Introduction: Graph Neural Network本文介绍的是GNN方面入门级别的知识, 其

ConvBERT: Improving BERT with Span-based Dynamic Convolution 本文前置知识: Light Weight Convolution: 详见基于轻量级卷积和动态卷积替代的注意力机制.

本文前置知识: BERT(Transformer Encoder). PPKE: Knowledge Representation Learning by Path-based Pre-training本文是论文PPKE: Know

Argparse和LoggingArgparse和Logging是Python实验中常用的两个模块. 之前没有整理过, 特此整理. ArgparseArgparse是用来解析Python命令行的标准库. 框架大致使用框架如下: impor

本文前置知识: GNN Relational Reflection Entity Alignment本文是论文Relational Reflection Entity Alignment的阅读笔记和个人理解. 这是我第一次接触关于实

Realistic Re-evaluation of Knowledge Graph Completion Methods: An Experimental Study本文是论文Realistic Re-evaluation of Know

Can We Predict New Facts with Open Knowledge Graph Embeddings? A Benchmark for Open Link Prediction本文是论文Can We Predict N

Generative Adversarial Zero-Shot Relational Learning for Knowledge Graphs本文是论文Generative Adversarial Zero-Shot Relationa

本文前置知识: Self - Attention: 详见Transformer精讲. 2020.12.14: 修正错误. A Relational Memory-based Embedding Model for Triple Cl

本文前置知识: Depthwise Convolution: 详见深度可分离卷积与分组卷积. Attention: 详见Seq2Seq和Attention. Transformer: 详见Transformer精讲. 本文是论文PA

本文前置知识: BERT: 详见ELMo, GPT, BERT. 本文是论文KG-BERT: BERT for Knowledge Graph Completion的阅读笔记和个人理解. Basic Idea在先前的KGE方法中,