Implementation of the objective clustering inductive technology based on DBSCAN clustering algorithm

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44555601%3A13440%2F17%3A43893057" target="_blank" >RIV/44555601:13440/17:43893057 - isvavai.cz</a>

Výsledek na webu

<a href="http://ieeexplore.ieee.org/document/8098832/" target="_blank" >http://ieeexplore.ieee.org/document/8098832/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/STC-CSIT.2017.8098832" target="_blank" >10.1109/STC-CSIT.2017.8098832</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Implementation of the objective clustering inductive technology based on DBSCAN clustering algorithm

Popis výsledku v původním jazyce

The paper presents the results of the research of the clustering algorithm DBSCAN practical implementation within the framework of the objective clustering inductive technology. As experimental, the data Aggregation and Compound of the Computing school of the East Finland University and the gene expression sequences of lung cancer patients of the database ArrayExpres were used. The architecture of the objective clustering model has been developed. The implementation of the model involves the parallel data clustering on the two equal power subsets, which include the same quantity of pairwise similar objects. The choice of the solution about parameters of the algorithm determination has been carried out based on the minimum value of the external clustering quality criterion, which calculated as normalized difference of the internal clustering quality criteria for the two subsets

Název v anglickém jazyce

Implementation of the objective clustering inductive technology based on DBSCAN clustering algorithm

Popis výsledku anglicky

The paper presents the results of the research of the clustering algorithm DBSCAN practical implementation within the framework of the objective clustering inductive technology. As experimental, the data Aggregation and Compound of the Computing school of the East Finland University and the gene expression sequences of lung cancer patients of the database ArrayExpres were used. The architecture of the objective clustering model has been developed. The implementation of the model involves the parallel data clustering on the two equal power subsets, which include the same quantity of pairwise similar objects. The choice of the solution about parameters of the algorithm determination has been carried out based on the minimum value of the external clustering quality criterion, which calculated as normalized difference of the internal clustering quality criteria for the two subsets

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

N - Vyzkumna aktivita podporovana z neverejnych zdroju

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

Computer Science and Information Technology, Proceedings of the XII-th International Scientific and Technical Conference

ISBN

978-1-5386-1638-3

ISSN

—

e-ISSN

neuvedeno

Počet stran výsledku

5

Strana od-do

479-484

Název nakladatele

Lviv Polytechnic National University

Místo vydání

Lviv

Místo konání akce

Lviv, Ukraine

Datum konání akce

5. 9. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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