@prefix owl: <http://www.w3.org/2002/07/owl#> .
@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#> .

<http://data.loterre.fr/ark:/67375/8LP> a owl:Ontology, skos:ConceptScheme .
<http://data.loterre.fr/ark:/67375/8LP-BKV07MF4-4>
  skos:prefLabel "problème d'apprentissage"@fr, "learning problem"@en ;
  a skos:Concept ;
  skos:narrower <http://data.loterre.fr/ark:/67375/8LP-QMZ4RRSM-J> .

<http://data.loterre.fr/ark:/67375/8LP-QMZ4RRSM-J>
  skos:inScheme <http://data.loterre.fr/ark:/67375/8LP> ;
  skos:prefLabel "terme de bruit"@fr, "noise term"@en ;
  skos:broader <http://data.loterre.fr/ark:/67375/8LP-BKV07MF4-4> ;
  skos:hiddenLabel "Terme de bruit"@fr, "Noise term"@en ;
  skos:example "To enhance the accuracy in translating multi-word or unknown terms it should be worthy to employ more effective techniques such as word segmentation and language model to filter out noise terms and extract complete translation candidates. (Lu, Chien & Lee, 2003)"@en, "However negative labeled examples (i.e. noise terms) are hard to acquire because we do not know which term is not an opinion word or target. (Xu, Liu & Zhao, 2014)"@en, "This network also helps load balancing by introducing a noise term. (Bi, Cheng, Li, Qu, Shen, Qi, Pan & Jiang, 2021)"@en ;
  a skos:Concept ;
  dc:modified "2024-06-14T07:01:43"^^xsd:dateTime .