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Precomputed Word Embeddings for 15+ Languages

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F21%3A00123246" target="_blank" >RIV/00216224:14330/21:00123246 - isvavai.cz</a>

  • Result on the web

    <a href="https://raslan2021.nlp-consulting.net/" target="_blank" >https://raslan2021.nlp-consulting.net/</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Precomputed Word Embeddings for 15+ Languages

  • Original language description

    Word embeddings serve as an useful resource for many downstream natural language processing tasks. The embeddings map or embed the lexicon of a language onto a vector space, in which various operations can be carried out easily using the established machinery of linear algebra. The unbounded nature of the language can be problematic and word embeddings provide a way of compressing the words into a manageable dense space. The position of a word in the vector space is given by the context the word appears in, or, as the distributional hypothesis postulates, a word is characterized by the company it keeps [2]. As similar words appear in similar contexts, their positions will also be close to each other in the embedding vector space. Because of this many useful semantical properties of words are preserved in the embedding vector space.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10200 - Computer and information sciences

Result continuities

  • Project

    <a href="/en/project/LM2018101" target="_blank" >LM2018101: Digital Research Infrastructure for the Language Technologies, Arts and Humanities</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2021

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Recent Advances in Slavonic Natural Language Processing (RASLAN 2021)

  • ISBN

    9788026316701

  • ISSN

    2336-4289

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    41-46

  • Publisher name

    Tribun EU

  • Place of publication

    Brno

  • Event location

    Brno

  • Event date

    Jan 1, 2021

  • Type of event by nationality

    EUR - Evropská akce

  • UT code for WoS article