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
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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
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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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
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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
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