Fast and exact fixed-radius neighbor search based on sorting

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F24%3A10491220" target="_blank" >RIV/00216208:11320/24:10491220 - isvavai.cz</a>

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=pJtICrozOZ" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=pJtICrozOZ</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.7717/peerj-cs.1929" target="_blank" >10.7717/peerj-cs.1929</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Fast and exact fixed-radius neighbor search based on sorting

Popis výsledku v původním jazyce

Fixed -radius near neighbor search is a fundamental data operation that retrieves all data points within a user -specified distance to a query point. There are efficient algorithms that can provide fast approximate query responses, but they often have a very compute -intensive indexing phase and require careful parameter tuning. Therefore, exact brute force and tree -based search methods are still widely used. Here we propose a new fixed -radius near neighbor search method, called SNN, that significantly improves over brute force and tree -based methods in terms of index and query time, provably returns exact results, and requires no parameter tuning. SNN exploits a sorting of the data points by their first principal component to prune the query search space. Further speedup is gained from an efficient implementation using high-level basic linear algebra subprograms (BLAS). We provide theoretical analysis of our method and demonstrate its practical performance when used standalone and when applied within the DBSCAN clustering algorithm.

Název v anglickém jazyce

Fast and exact fixed-radius neighbor search based on sorting

Popis výsledku anglicky

Fixed -radius near neighbor search is a fundamental data operation that retrieves all data points within a user -specified distance to a query point. There are efficient algorithms that can provide fast approximate query responses, but they often have a very compute -intensive indexing phase and require careful parameter tuning. Therefore, exact brute force and tree -based search methods are still widely used. Here we propose a new fixed -radius near neighbor search method, called SNN, that significantly improves over brute force and tree -based methods in terms of index and query time, provably returns exact results, and requires no parameter tuning. SNN exploits a sorting of the data points by their first principal component to prune the query search space. Further speedup is gained from an efficient implementation using high-level basic linear algebra subprograms (BLAS). We provide theoretical analysis of our method and demonstrate its practical performance when used standalone and when applied within the DBSCAN clustering algorithm.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10102 - Applied mathematics

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

PeerJ Computer Science

ISSN

2376-5992

e-ISSN

2376-5992

Svazek periodika

10

Číslo periodika v rámci svazku

March 29, 2024

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

23

Strana od-do

e1929

Kód UT WoS článku

001194752800001

EID výsledku v databázi Scopus

2-s2.0-85190374252