CLUSTERING THE MOBILE PHONE POSITIONS BASED ON SUFFIX TREE AND SELF-ORGANIZING MAPS
The result's identifiers
Result code in 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>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
CLUSTERING THE MOBILE PHONE POSITIONS BASED ON SUFFIX TREE AND SELF-ORGANIZING MAPS
Original language description
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.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Neural Network World
ISSN
1210-0552
e-ISSN
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Volume of the periodical
22
Issue of the periodical within the volume
4
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
16
Pages from-to
371-386
UT code for WoS article
000309320500005
EID of the result in the Scopus database
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