SiLi Index: Data Structure for Fast Vector Space Searching

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F19%3A00111665" target="_blank" >RIV/00216224:14330/19:00111665 - isvavai.cz</a>
Result on the web
<a href="https://nlp.fi.muni.cz/raslan/2019/paper07-herman.pdf" target="_blank" >https://nlp.fi.muni.cz/raslan/2019/paper07-herman.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
SiLi Index: Data Structure for Fast Vector Space Searching
Original language description
Nearest neighbor queries in high-dimensional spaces are ex-pensive. In this article, we propose a method of building and querying astand-alone data structure, SiLi (SimilarityList) Index, which supports ap-proximating the results of k-NN queries in high-dimensional spaces, whileusing a significantly reduced amount of system memory and processortime compared to the usual brute-force search methods.
Czech name
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Czech description
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Project
<a href="/en/project/LM2015071" target="_blank" >LM2015071: Language Research Infrastructure in the Czech Republic</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of the Thirteenth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2019
ISBN
9788026315308
ISSN
2336-4289
e-ISSN
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Number of pages
6
Pages from-to
111-116
Publisher name
Tribun EU
Place of publication
Brno
Event location
Brno
Event date
Jan 1, 2019
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
000604899800013

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