Scaling to Billion-plus Word Corpora

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F09%3A00035368" target="_blank" >RIV/00216224:14330/09:00035368 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Scaling to Billion-plus Word Corpora
Original language description
Most phenomena in natural languages are distributed in accordance with Zipf's law, so many words, phrases and other items occur rarely and we need very large corpora to provide evidence about them. Previous work shows that it is possible to create very large (multi-billion word) corpora from the web. The usability of such corpora is often limited by duplicate contents and a lack of efficient query tools. This paper describes BiWeC, a Big Web Corpus of English texts currently comprising 5.5b words fullyprocessed, and with a target size of 20b. We present a method for detecting near-duplicate text documents in multi-billion-word text collections and describe how one corpus query tool, the Sketch Engine, has been re-engineered to efficiently encode, process and query such corpora on low-cost hardware.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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