CLUSTERING THE MOBILE PHONE POSITIONS BASED ON SUFFIX TREE AND SELF-ORGANIZING MAPS

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F12%3A86084586" target="_blank" >RIV/61989100:27240/12:86084586 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

CLUSTERING THE MOBILE PHONE POSITIONS BASED ON SUFFIX TREE AND SELF-ORGANIZING MAPS

Popis výsledku v původním jazyce

In this article we present a novel method for mobile phone positioning using a vector space model, suffix trees and an information retrieval approach. The algorithm is based on a database of previous measurements which are used as an index which looks for the nearest neighbor toward the query measurement. The accuracy of the algorithm is, in most cases, good enough to accomplish the E9-1-1 standards requirements on tested data. In addition, we are trying to look at the clusters of patterns that we havecreated from measured data and we have reflected them to the map. We use Self-Organizing Maps for these purposes.

Název v anglickém jazyce

CLUSTERING THE MOBILE PHONE POSITIONS BASED ON SUFFIX TREE AND SELF-ORGANIZING MAPS

Popis výsledku anglicky

In this article we present a novel method for mobile phone positioning using a vector space model, suffix trees and an information retrieval approach. The algorithm is based on a database of previous measurements which are used as an index which looks for the nearest neighbor toward the query measurement. The accuracy of the algorithm is, in most cases, good enough to accomplish the E9-1-1 standards requirements on tested data. In addition, we are trying to look at the clusters of patterns that we havecreated from measured data and we have reflected them to the map. We use Self-Organizing Maps for these purposes.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název periodika

Neural Network World

ISSN

1210-0552

e-ISSN

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Svazek periodika

22

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

16

Strana od-do

371-386

Kód UT WoS článku

000309320500005

EID výsledku v databázi Scopus

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