@prefix skos: <http://www.w3.org/2004/02/skos/core#> .
@prefix dc: <http://purl.org/dc/terms/> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .
@prefix ltk: <http://data.loterre.fr/ark:/67375/LTK> .
@prefix owl: <http://www.w3.org/2002/07/owl#> .

<http://data.loterre.fr/ark:/67375/8LP-GKGZ083L-Z>
  skos:prefLabel "plongement"@fr, "embedding"@en ;
  a skos:Concept ;
  skos:narrower <http://data.loterre.fr/ark:/67375/8LP-ZTVBBBWR-N> .

<http://data.loterre.fr/ark:/67375/8LP-ZTVBBBWR-N>
  skos:prefLabel "plongement de phrases"@fr, "sentence embedding"@en ;
  skos:example "Sentence embeddings are extracted from each encoder. (Feng, Yang, Cer, Arivazhagan & Wang, 2022)"@en, "We propose to learn distributed sentence representation using the text's visual features as input. (Liu, Wang & Yin, 2020)"@en, "The distributed sentence representation is assigned to capture both syntactic and semantic information. (Lin, Liu, Yang, Li, Zhou & Li, 2015)"@en, "The sentence embedding is obtained by averaging the embedding vectors of all words in the sentence. (Kumar, Sethi, Akhtar, Ekbal, Biemann & Bhattacharyya, 2017)"@en, "Li and Hovy (2014) propose a neural network coherence model which employs distributed sentence representation and then predict the probability of whether a sequence of sentences is coherent or not. (Lin, Liu, Yang, Li, Zhou & Li, 2015)"@en ;
  skos:hiddenLabel "Plongement de phrases"@fr, "Sentence embedding"@en ;
  dc:modified "2024-05-29T06:15:31"^^xsd:dateTime ;
  skos:exactMatch ltk:-N94S63GB-D, <https://www.wikidata.org/wiki/Q29043221> ;
  skos:altLabel "distributed sentence representation"@en ;
  skos:definition "Vector representations of text at the sentence level. (Loterre)"@en, "Représentations vectorielles calculées pour des phrases."@fr ;
  skos:inScheme <http://data.loterre.fr/ark:/67375/8LP> ;
  skos:broader <http://data.loterre.fr/ark:/67375/8LP-GKGZ083L-Z> ;
  a skos:Concept .

<http://data.loterre.fr/ark:/67375/8LP> a owl:Ontology, skos:ConceptScheme .