D 2019

SiLi Index: Data Structure for Fast Vector Space Searching

HERMAN, Ondřej and Pavel RYCHLÝ

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

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10200 1.2 Computer and information sciences

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

RIV identification code

RIV/00216224:14330/19:00111665

Organization unit

Faculty of Informatics

ISBN

978-80-263-1530-8

ISSN

UT WoS

000604899800013

Keywords in English

word embeddings; vector space; semantic similarity
Změněno: 15/5/2024 01:31, RNDr. Pavel Šmerk, Ph.D.

Abstract

V originále

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 project
Name: Jazyková výzkumná infrastruktura v České republice (Acronym: LINDAT-Clarin)
Investor: Ministry of Education, Youth and Sports of the CR