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Діалектні особливості щоденника-хроніки "Війна" І. Бажанського ; Диалектные особенности дневника-хроники "Война" И. Бажанского ; Dialectical features of I. Bazhansky's diary-chronicle "War"
Moysey, A.; Мойсей, Антоній; Моисей, А.. - : Актуальні питання суспільних наук та історії медицини, 2021
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An analysis of the features of words that influence vocabulary difficulty. https://www.mdpi.com/2227-7102/9/1/8
Hiebert, Elfrieda; Scott, Judith; Castaneda, Ruben. - : eScholarship, University of California, 2021
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WELFake dataset for fake news detection in text data ...
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WELFake dataset for fake news detection in text data ...
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СТРУКТУРНЫЕ ОСОБЕННОСТИ АНГЛИЙСКИХ ЮРИДИЧЕСКИХ ТЕРМИНОВ, ОБОЗНАЧАЮЩИХ ВИДЫ ПРЕСТУПЛЕНИЙ ... : STRUCTURAL FEAUTURES OF ENGLISH LEGAL TERMS DESCRIBING TYPES OF CRIMES ...
Т.Н. Малиновская. - : Мир науки, культуры, образования, 2021
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RESEARCH OUTCOMES AND RECOMMENDATIONS ON CREATING ETYMOLOGICAL DICTIONARY ...
Rakhimova, G.; Yuldashev, E.. - : The Scientific Heritage, 2021
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СЕМАНТИЧЕСКИЕ ОСОБЕННОСТИ ЦВЕТООБОЗНАЧЕНИЙ «СИНИЙ» И «ЗЕЛЁНЫЙ» В КИТАЙСКОМ И АНГЛИЙСКОМ ЯЗЫКАХ ...
ШЕВЧУК ОКСАНА ПАВЛОВНА; КАРПЕНКО СЕРГЕЙ ЮРЬЕВИЧ. - : Современное педагогическое образование, 2020
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Гимнография на современном сербском языке: лексика, стилистика, интертекстуальность ... : Himnography in the modern Serbian Language: Lexicon, Stylistics, Interculturality ...
Кончаревич, К.. - : Свято-Филаретовский православно-христианский институт, 2020
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How Children with Autism Spectrum Disorder, Developmental Language Disorder, and Typical Language Learn to Produce Global and Local Semantic Features
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РЕЧЕВОЙ ПОРТРЕТ НОСИТЕЛЯ НАРОДНОГО ЯЗЫКА ВОРОНЕЖСКОЙ ОБЛАСТИ ...
Недоступова Л.В.. - : НАУЧНЫЙ ЖУРНАЛ СОВРЕМЕННЫЕ ЛИНГВИСТИЧЕСКИЕ И МЕТОДИКО-ДИДАКТИЧЕСКИЕ ИССЛЕДОВАНИЯ, 2020
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How Children with Autism Spectrum Disorder, Developmental Language Disorder, and Typical Language Learn to Produce Global and Local Semantic Features
In: Brain Sciences ; Volume 10 ; Issue 4 (2020)
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Prediction of Alzheimer's disease and semantic dementia from scene description: toward better language and topic generalization
Ivensky, Ilya. - 2020
Abstract: La segmentation des données par la langue et le thème des tests psycholinguistiques devient de plus en plus un obstacle important à la généralisation des modèles de prédiction. Cela limite notre capacité à comprendre le cœur du dysfonctionnement linguistique et cognitif, car les modèles sont surajustés pour les détails d'une langue ou d'un sujet particulier. Dans ce travail, nous étudions les approches potentielles pour surmonter ces limitations. Nous discutons des propriétés de divers modèles de plonjement de mots FastText pour l'anglais et le français et proposons un ensemble des caractéristiques, dérivées de ces propriétés. Nous montrons que malgré les différences dans les langues et les algorithmes de plonjement, un ensemble universel de caractéristiques de vecteurs de mots indépendantes de la langage est capable de capturer le dysfonctionnement cognitif. Nous soutenons que dans le contexte de données rares, les caractéristiques de vecteur de mots fabriquées à la main sont une alternative raisonnable pour l'apprentissage des caractéristiques, ce qui nous permet de généraliser sur les limites de la langue et du sujet. ; Data segmentation by the language and the topic of psycholinguistic tests increasingly becomes a significant obstacle for generalization of predicting models. It limits our ability to understand the core of linguistic and cognitive dysfunction because the models overfit the details of a particular language or topic. In this work, we study potential approaches to overcome such limitations. We discuss the properties of various FastText word embedding models for English and French and propose a set of features derived from these properties. We show that despite the differences in the languages and the embedding algorithms, a universal language-agnostic set of word-vector features can capture cognitive dysfunction. We argue that in the context of scarce data, the hand-crafted word-vector features is a reasonable alternative for feature learning, which allows us to generalize over the language and topic boundaries.
Keyword: Applied Sciences - Artificial Intelligence / Sciences appliqués et technologie - Intelligence artificielle (UMI : 0800); Caractéristiques multilingues; Cognitive impairment; Computational linguistics; Déficience cognitive; Linguistique informatique; Multilingual features; Natural language processing; Plongement de mots; Traitement automatique des langues; Word embedding
URL: http://hdl.handle.net/1866/24317
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13
Il valore delle parole
De Mauro, Tullio; Gensini, Stefano (Verfasser von ergänzendem Text). - [Roma] : Treccani, 2019
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UB Frankfurt Linguistik
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Perceptual features predict word frequency asymmetry across modalities.
In: Attention, perception & psychophysics, vol 81, iss 4 (2019)
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An analysis of the features of words that influence vocabulary difficulty. https://www.mdpi.com/2227-7102/9/1/8
In: Scott, Judith; Hiebert, Elfrieda; Castaneda, Ruben; & Spichtig, A. (2019). An analysis of the features of words that influence vocabulary difficulty. https://www.mdpi.com/2227-7102/9/1/8. Education Sciences. UC Santa Cruz: Retrieved from: http://www.escholarship.org/uc/item/5dg5k95n (2019)
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An Analysis of the Features of Words That Influence Vocabulary Difficulty
In: Education Sciences ; Volume 9 ; Issue 1 (2019)
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ИНДИВИДУАЛЬНОЕ СЛОВОТВОРЧЕСТВО ПОЭТА ВАСИЛИЯ КАМЕНСКОГО ... : INDIVIDUAL WORD CREATION OF THE POET VASILY KAMENSKY ...
Khalyavina, Darya; Droga, Marina. - : Cross Cultural Studies: Education and Science, 2018
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The shape of things to come in speech production: visual form interference during lexical access
de Zubicaray, Greig I.; McLean, Mia; Oppermann, Frank. - : Sage Publications, 2018
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Syntactic Interactions with Information Structure in Squliq Atayal
Liu, Kun-Long. - 2017
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Biases in phonological processing and learning ; Les biais dans le traitement et l'apprentissage phonologiques
Martin, Alexander. - : HAL CCSD, 2017
In: https://tel.archives-ouvertes.fr/tel-01939096 ; Psychology. Université Paris sciences et lettres, 2017. English. ⟨NNT : 2017PSLEE071⟩ (2017)
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