An Evaluation of the Objective Clustering Inductive Technology Effectiveness Implemented Using Density-Based and Agglomerative Hierarchical Clustering Algorithms
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44555601%3A13440%2F20%3A43894675" target="_blank" >RIV/44555601:13440/20:43894675 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-030-26474-1_37" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-26474-1_37</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-26474-1_37" target="_blank" >10.1007/978-3-030-26474-1_37</a>
Alternative languages
Result language
angličtina
Original language name
An Evaluation of the Objective Clustering Inductive Technology Effectiveness Implemented Using Density-Based and Agglomerative Hierarchical Clustering Algorithms
Original language description
The paper presents the results of the research concerning comparison analysis of the efectiveness of OPTICS and DBSCAN density-based and agglonarative hierarchical clustering algorithms within the framework of the objective clustering inductive technology. Implementation of this technology allows us to determine the optimal parameters of appropriate clustering algorithm in terms of the maximum values of the complex balance criterion which contains as the components both the internal and the external clustering quality criteria. The data from the Computing School of East Finland University database were used as the experimental one during the simulation process. The results of the simulation have shown high effectiveness of the proposed technique. The investigated objects were divided into clusters correctly in all cases. Moreover, the results of the simulation have shown also higher effectiveness of the density-based clustering algorithms in comparison with agglomerative hierarchical algorithm use due to more level of the detail during the objects clustering
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Advances in Intelligent Systems and Computing
ISBN
978-3-030-26473-4
ISSN
2194-5357
e-ISSN
2194-5365
Number of pages
22
Pages from-to
532-553
Publisher name
Springer Verlag
Place of publication
Cham
Event location
Kherson
Event date
May 21, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000623482600037