|
gptkbp:instanceOf
|
knowledge graph embedding model
|
|
gptkbp:assumes
|
relations as translations in embedding space
|
|
gptkbp:citation
|
high
|
|
gptkbp:designedFor
|
knowledge graph completion
|
|
gptkbp:developedBy
|
gptkb:Alberto_Garcia-Duran
gptkb:Oksana_Yakhnenko
gptkb:Jason_Weston
gptkb:Nicolas_Usunier
gptkb:Antoine_Bordes
|
|
gptkbp:embeddingType
|
translational distance model
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
TransE
|
|
gptkbp:influenced
|
gptkb:KG2E
gptkb:TransD
gptkb:TransH
gptkb:TransR
|
|
gptkbp:input
|
triples
|
|
gptkbp:limitation
|
difficulty modeling 1-to-N, N-to-1, N-to-N relations
|
|
gptkbp:objective
|
minimize distance between h + r and t
|
|
gptkbp:openSource
|
gptkb:AmpliGraph
gptkb:OpenKE
gptkb:PyKEEN
|
|
gptkbp:platform
|
vector space embedding
|
|
gptkbp:publicationYear
|
2013
|
|
gptkbp:publishedIn
|
gptkb:NIPS_2013
|
|
gptkbp:relatedTo
|
gptkb:artificial_intelligence
gptkb:machine_learning
gptkb:knowledge_representation
representation learning
embedding
|
|
gptkbp:usedFor
|
link prediction
relation extraction
entity classification
|
|
gptkbp:bfsParent
|
gptkb:Antoine_Bordes
|
|
gptkbp:bfsLayer
|
6
|