HERMAN, Ondřej and Pavel RYCHLÝ. SiLi Index: Data Structure for Fast Vector Space Searching. In Horák, Aleš and Rychlý, Pavel and Rambousek, Adam. Proceedings of the Thirteenth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2019. Brno: Tribun EU, 2019, p. 111-116. ISBN 978-80-263-1530-8.
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Basic information
Original name SiLi Index: Data Structure for Fast Vector Space Searching
Authors HERMAN, Ondřej (203 Czech Republic, belonging to the institution) and Pavel RYCHLÝ (203 Czech Republic, belonging to the institution).
Edition Brno, Proceedings of the Thirteenth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2019, p. 111-116, 6 pp. 2019.
Publisher Tribun EU
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10200 1.2 Computer and information sciences
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
WWW URL
RIV identification code RIV/00216224:14330/19:00111665
Organization unit Faculty of Informatics
ISBN 978-80-263-1530-8
ISSN 2336-4289
UT WoS 000604899800013
Keywords in English word embeddings; vector space; semantic similarity
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 15/5/2024 01:31.
Abstract
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.
Links
LM2015071, research and development projectName: Jazyková výzkumná infrastruktura v České republice (Acronym: LINDAT-Clarin)
Investor: Ministry of Education, Youth and Sports of the CR
PrintDisplayed: 11/10/2024 14:26