filmov
tv
Knowledge Graph Embedding - Dec 2021
Показать описание
An intro to Knowledge Graphs, based on our knowledge of Graph Neural Networks. A simple example provides an easy pathway to Knowledge Graphs and training of Knowledge Graphs (AI).
Knowledge graphs (KG) are data structures that store information about different entities (nodes) and their relations (edges). A common approach of using KG in various machine learning tasks is to compute knowledge graph embeddings.
A knowledge graph (KG) is a directed heterogeneous multigraph whose node and relation types have domain-specific semantics. KG allow us to encode the knowledge into a form that is human interpretable and amenable to automated analysis and inference.
Two models for Knowledge Graph Embeddings are presented and expained: TransE and TransR.
00:00 Remember word embedding?
01:53 Knowledge graph embedding
03:18 Simple knowledge graph
06:52 Key idea
08:50 Closeness
12:20 TransE explained
13:18 Knowledge graph embeddings
15:18 TransR explained
#knowledgegraph
#embedding
#Intro2KnowledgeGraphs
#graphs
#neuralnetworks
#ai
#machinelearningwithpython
#convolutionalneuralnetwork
#jupyterlab
#dgl
#word2vec
Knowledge graphs (KG) are data structures that store information about different entities (nodes) and their relations (edges). A common approach of using KG in various machine learning tasks is to compute knowledge graph embeddings.
A knowledge graph (KG) is a directed heterogeneous multigraph whose node and relation types have domain-specific semantics. KG allow us to encode the knowledge into a form that is human interpretable and amenable to automated analysis and inference.
Two models for Knowledge Graph Embeddings are presented and expained: TransE and TransR.
00:00 Remember word embedding?
01:53 Knowledge graph embedding
03:18 Simple knowledge graph
06:52 Key idea
08:50 Closeness
12:20 TransE explained
13:18 Knowledge graph embeddings
15:18 TransR explained
#knowledgegraph
#embedding
#Intro2KnowledgeGraphs
#graphs
#neuralnetworks
#ai
#machinelearningwithpython
#convolutionalneuralnetwork
#jupyterlab
#dgl
#word2vec
0:16:59
Knowledge Graph Embedding - Dec 2021
0:05:03
AKBC 2020: Paper: Knowledge Graph Embedding Compression
0:14:49
A Casual Introduction to Knowledge Graph Embedding Models (Research Paper Breakdown)
0:12:17
4.10 - Knowledge Graph Embeddings
0:05:36
What is a Knowledge Graph?
0:07:39
The math & business of Knowledge Graph Embedding in less than 10 minutes
0:37:34
096 From Node to Knowledge Graph Embeddings - NODES2022 - Tomaz Bratanic
0:04:46
AKBC 2020: Paper: Dolores: Deep Contextualized Knowledge Graph Embeddings
0:02:21
AKBC 2021: Paper: Behavioral Testing of Knowledge Graph Embedding Models for Link Prediction
3:15:11
Knowledge Graph Embeddings Tutorial From Theory to Practice
0:21:10
First look at Knowledge Graph Embedding (w/ simple Jupyter NB dgl-ke)
0:09:30
KR 2021 - Do Embeddings Actually Capture Knowledge Graph Semantics?
0:08:02
Re-evaluating Knowledge Graph Embedding Models Performance on Domain Specific Datasets
0:04:31
scaling knowledge graph embedding models for link prediction
3:15:11
Knowledge Graph Embeddings Tutorial: From Theory to Practice
0:08:48
CSCI 635 Final Presentation: An Analysis of Convolutional 2D Knowledge Graph Embedding
0:52:07
Graph Gurus 47: Graph Data Science with Knowledge Graph Embeddings
0:19:40
Graph Embeddings (Embeddings in NLP)
0:00:40
Knowledge Graph Embedding Visualisation of Drug Labels
0:06:46
NodePiece code for Knowledge Graphs in Python, clever Node embedding in 2022
0:01:32
Neo4j Graph Embeddings
1:00:10
Knowledge Graph Representation: From Recent Models towards a Theoretical Understanding.
0:02:41
AKBC 2021: Paper: A Joint Training Framework for Open-World Knowledge Graph Embeddings
0:34:17
Knowledge Graph Embeddings and ES for large scale content based Recommender Systems by Mohameth Fran
Комментарии