Knowledge graph embedding
In representation learning, knowledge graph embedding (KGE), also referred to as knowledge representation learning (KRL), or multi-relation learning, is a machine learning task of learning a low-dimensional representation of a knowledge graph's entities and relations while preserving their semantic meaning. Leveraging their embedded representation, knowledge graphs (KGs) can be used for various applications such as link prediction, , , clustering, and relation extraction.
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- enIn representation learning, knowledge graph embedding (KGE), also referred to as knowledge representation learning (KRL), or multi-relation learning, is a machine learning task of learning a low-dimensional representation of a knowledge graph's entities and relations while preserving their semantic meaning. Leveraging their embedded representation, knowledge graphs (KGs) can be used for various applications such as link prediction, , , clustering, and relation extraction.
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- enIn representation learning, knowledge graph embedding (KGE), also referred to as knowledge representation learning (KRL), or multi-relation learning, is a machine learning task of learning a low-dimensional representation of a knowledge graph's entities and relations while preserving their semantic meaning. Leveraging their embedded representation, knowledge graphs (KGs) can be used for various applications such as link prediction, , , clustering, and relation extraction.
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- Knowledge graph embedding
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- enKnowledge graph embedding
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- github.com/Accenture/AmpliGraph
- github.com/awslabs/dgl-ke
- github.com/thunlp/Fast-TransX
- wordnet.princeton.edu/
- github.com/uma-pi1/kge
- github.com/tranhungnghiep/MEI-KGE%7CMEI-KGE
- github.com/tranhungnghiep/MEIM-KGE%7CMEIM-KGE
- ogb.stanford.edu
- github.com/thunlp/OpenKE
- github.com/pykeen/pykeen
- github.com/Sujit-O/pykg2vec
- github.com/mnick/scikit-kge
- github.com/torchkge-team/torchkge
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- Analogical
- Asymmetric relation
- Batch learning
- Benchmark (computing)
- Canonical polyadic decomposition
- Capsule neural network
- Category:Graph algorithms
- Category:Information science
- Category:Knowledge graphs
- Category:Machine learning
- Cluster analysis
- Complex vector space
- Convolutional layer
- Deep neural network
- Drug repurposing
- Ellipse
- Embedding
- Entity recognition
- Euclidean distance
- Euler's identity
- File:KG-Embedding.svg
- File:KnowledgeGraphEmbedding.png
- File:TransE.pdf
- Fourier transform
- Graph embedding
- Hadamard product (matrices)
- Hermitian product
- Hyperplane
- Inner product space
- Knowledge base
- Knowledge extraction
- Knowledge graph
- Lie group
- Link prediction
- Machine learning
- Mahalanobis distance
- Many-to-many
- Many-to-one relation
- One-to-many (data model)
- Overfitting
- Recommender system
- Recurrent neural network
- Reinforcement learning
- Relation extraction
- Representation learning
- Semantics
- Spherical
- Statistical relational learning
- Tensor
- Torus
- Training set
- Triple Classification
- Tucker decomposition
- Vector sum
- Word2vec
- SameAs
- 32iWF
- Incorporamento del grafo di conoscenza
- Q33003557
- Subject
- Category:Graph algorithms
- Category:Information science
- Category:Knowledge graphs
- Category:Machine learning
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- Knowledge graph embedding?oldid=1114013093&ns=0
- WikiPageLength
- 53431
- Wikipage page ID
- 67944487
- Wikipage revision ID
- 1114013093
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- Template:GitHub
- Template:Scholia
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