Knowledge Graph Embedding - Dec 2021

code_your_own_AI
code_your_own_AI
11.6 هزار بار بازدید - 3 سال پیش - An intro to Knowledge Graphs,
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
3 سال پیش در تاریخ 1400/09/30 منتشر شده است.
11,659 بـار بازدید شده
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