knowledge graph embedding
Machine learning embedding of knowledge graph
In representation learning, knowledge graph embedding (KGE), also called 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 meaning. Leveraging their embedded representation, knowledge graphs can be used for various applications such as link prediction, triple classification, entity recognition, clustering, and relation extraction.
Nº Q33003557 ★
Común · Saberes
knowledge graph embedding
Machine learning embedding of knowledge graph
In representation learning, knowledge graph embedding (KGE), also called 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 meaning. Leveraging their embedded representation, knowledge graphs can be used for various applications such as link prediction, triple classification, entity recognition, clustering, and relation extraction.
En Wikipedia
Texto en inglés Aún no hay artículo en tu idioma: extracto en inglés.
In representation learning, knowledge graph embedding (KGE), also called 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 meaning. Leveraging their embedded representation, knowledge graphs can be used for various applications such as link prediction, triple classification, entity recognition, clustering, and relation extraction.
Texto: Wikipedia en inglés, CC BY-SA 4.0. · Imagen: EdoardoRamalli (CC BY-SA 4.0) ·
Cartas cercanas
-
r
representación del conocimiento
Campo de la inteligencia artificial en la representación de información en una forma que un sistema informático puede utilizar para resolver tareas complejas
Nº Q3478658 ★
Sin ofertas
-
k
knowledge map
Graphical representation of the distribution of knowledge in an organization
Nº Q1371259 ★
Sin ofertas
-
L
Learning with errors
Problem in machine learning that is conjectured to be hard to solve. Introduced by Oded Regev in 2005, it is a generalization of the parity learning problem
Nº Q6510239 ★
Sin ofertas
-
M
Meta-learning
Aspect of metacognition
Nº Q6822310 ★
Sin ofertas
-
K
Knowledge Query and Manipulation Language
Language and protocol for communication among software agents and knowledge-based systems
Nº Q613270 ★
Sin ofertas
-
Kaggle
Comunidad en línea de científicos de datos y profesionales del aprendizaje automático
Nº Q10996045 ★★
Sin ofertas