%D8%AA%D8%B6%D9%85%D9%8A%D9%86_%D8%A7%D9%84%D9%83%D9%84%D9%85%D8%A7%D8%AAVno%C5%99en%C3%AD_slovWord_embeddingWord_embeddingWord_embeddingWord_embeddingWord_embedding%D0%92%D0%B5%D0%BA%D1%82%D0%BE%D1%80%D0%BD%D0%BE%D0%B5_%D0%BF%D1%80%D0%B5%D0%B4%D1%81%D1%82%D0%B0%D0%B2%D0%BB%D0%B5%D0%BD%D0%B8%D0%B5_%D1%81%D0%BB%D0%BE%D0%B2Q18395344%E8%AF%8D%E5%B5%8C%E5%85%A5
about
Efficient Estimation of Word Representations in Vector SpaceLearning Sentiment-Specific Word Embedding for Twitter Sentiment ClassificationA Study of Neural Word Embeddings for Named Entity Recognition in Clinical TextEigenwords: Spectral Word EmbeddingsPharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster featuresSentiment Embeddings with Applications to Sentiment AnalysisNatural Language Processing (almost) from ScratchEnriching Word Vectors with Subword InformationBag of Tricks for Efficient Text ClassificationNeural word embedding as implicit matrix factorizationLinguistic Regularities in Continuous Space Word RepresentationsWhat can you do with a rock? Affordance extraction via word embeddingsA unified architecture for natural language processing: deep neural networks with multitask learningCombining Word and Entity Embeddings for Entity LinkingContext encoders as a simple but powerful extension of word2vecDependency-based word embeddingsSpanish word vectors from WikipediaAn Ensemble Method to Produce High-Quality Word EmbeddingsMassively Multilingual Word EmbeddingsWebVectors: A Toolkit for Building Web Interfaces for Vector Semantic ModelsBuilding Web-Interfaces for Vector Semantic Models with the WebVectors ToolkitA Simple Approach to Learn Polysemous Word EmbeddingsJoint Learning of the Embedding of Words and Entities for Named Entity DisambiguationAutoExtend: Extending Word Embeddings to Embeddings for Synsets and LexemesFrom Word Embeddings to Item RecommendationBiomedical event trigger detection by dependency-based word embeddingSemantics derived automatically from language corpora contain human-like biasesDetecting negation and scope in Chinese clinical notes using character and word embedding.Fracture Mechanics Method for Word Embedding Generation of Neural Probabilistic Linguistic Model.Mining e-cigarette adverse events in social media using Bi-LSTM recurrent neural network with word embedding representation.The strange geometry of skip-gram with negative samplingProblems With Evaluation of Word Embeddings Using Word Similarity TasksSimplifying drug package leaflets written in Spanish by using word embedding.Open semantic analysis: The case of word level semantics in DanishPolyglot: Distributed Word Representations for Multilingual NLPUsing Word Embeddings for Search in Linked Data with OntodiaSentence Answer Selection for Open Domain Question Answering via Deep Word MatchingWord2Vec vs DBnary: Augmenting METEOR using Vector Representations or Lexical Resources?Towards the evaluation of feature embedding models of the fusional languagesEvaluating word embeddings with fMRI and eye-tracking
P921
Q24699014-47682d23-4333-8dc6-439a-5068473035c9Q28584914-6b2b91eb-4773-8723-368d-6d832c55f811Q28603788-9ec6b962-43a5-c186-df54-4c7bbb4ed9f6Q28622468-ee7a8639-48f6-7338-3b5e-55676f5464d3Q28645804-642AC8B5-A3ED-42B9-9B4E-DD0CB4BEEC24Q28660782-39f2a35b-45e6-2cbb-cba6-a57bba79f483Q28732639-9bd63a9a-4f17-547f-49b0-30dc6dbd9c18Q28775150-56b87782-4c9a-43b4-61a0-a274c70b4fe8Q28942761-89b9547d-4959-1f7f-f8fb-08b7b26bde65Q28949157-c4b8ef17-4130-7dd7-8f9f-beb578281613Q28949674-c25e87e1-41bc-d63f-1072-349a565ac6ccQ28971401-68fb53ca-4b2a-0393-e700-c7a678c093ccQ29046039-DF6EFBB3-76A0-4A93-8870-5DB7DE951AE0Q30095029-76e5201a-45a5-31df-d4b1-71b030e70071Q30232053-d3848d55-4159-0fb3-7eb2-fd45a0e0f44cQ31777138-21e4acf2-4ead-75f0-20ce-e1739700a250Q31888978-5824b92c-4ce9-c8eb-8e92-b06eaaa32866Q31897930-2045ce24-4d9a-6b5a-2034-00f9d8a333acQ32129681-45926e28-4e91-2d0a-bd1f-4f3bbc8420b2Q32132685-627bad52-4d17-32a2-f7b6-2081f1d3a917Q32138153-ac5c3fab-4743-4320-873c-65a90eaa28e5Q32786146-a58f5a66-4216-4acc-b543-433ad6971cf6Q32853234-3bc992d2-4386-cb8b-893f-496fd3910780Q32855945-c02f8e39-422c-d8f3-26b1-34413b9c6df3Q35264673-3312e99c-45d0-5131-90d1-f7241ffb3f04Q37167001-BE009F33-47EE-4097-A435-0F865D826667Q38378096-b9fb5f0d-43e6-3e4f-69f8-d72f775e6bdcQ38380042-13E0AB6C-85EB-4451-8361-B39CC974E334Q38386893-A27A75FC-A872-4C78-8E96-A2B7C47114BAQ38785777-CCE9759C-C0C1-4CB2-950A-C55390D0B769Q39378799-016581a4-4b2c-1864-dd88-9b6c6069840aQ39757803-a3a4a793-4ba9-27e9-8dd6-23f7caeda463Q42129732-1DDA2C14-34F0-4156-920D-915108DA7EB4Q42155754-253fbb4d-4e50-bedf-537e-52bd8e66e262Q42293702-a4432dfd-4c14-45c0-3a8b-4076ea3025baQ42309704-352ba7a9-4f7b-ddf8-1a21-4c3b40b6c86dQ43280738-2136d5eb-4a70-1dfd-58af-e6cf03f765f5Q43304158-8a1209b9-44e1-7910-1c18-7dff4c2eb4e5Q43547738-68a1068d-42a9-cc21-8327-034bbc888dbdQ43563495-3dfc00fe-4600-a2fa-ecb8-eeb0ff12cc2e
P921
description
method in natural language processing
@en
metode i natursprogsbehandling
@da
tecnica di elaborazione del linguaggio naturale
@it
подход к моделированию языка
@ru
name
Vnoření slov
@cs
Word embedding
@eu
Word embedding
@fr
ord-indlejring
@da
vektorisering av ord
@nn
vorto-enkorpigo
@eo
word embedding
@en
word embedding
@es
word embedding
@it
Вкладання слів
@uk
type
label
Vnoření slov
@cs
Word embedding
@eu
Word embedding
@fr
ord-indlejring
@da
vektorisering av ord
@nn
vorto-enkorpigo
@eo
word embedding
@en
word embedding
@es
word embedding
@it
Вкладання слів
@uk
altLabel
ord-embedding
@da
ordrepresentasjon
@nn
ordvektorisering
@nn
representasjon av ord
@nn
representasjon
@nn
vektorisering
@nn
word embeddings
@en
векторне представлення слів
@uk
prefLabel
Vnoření slov
@cs
Word embedding
@eu
Word embedding
@fr
ord-indlejring
@da
vektorisering av ord
@nn
vorto-enkorpigo
@eo
word embedding
@en
word embedding
@es
word embedding
@it
Вкладання слів
@uk
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