Growing neural gas based on data density
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10240396" target="_blank" >RIV/61989100:27240/18:10240396 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/18:10240396
Result on the web
<a href="https://link.springer.com/chapter/10.1007%2F978-3-319-99954-8_27" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-319-99954-8_27</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-99954-8_27" target="_blank" >10.1007/978-3-319-99954-8_27</a>
Alternative languages
Result language
angličtina
Original language name
Growing neural gas based on data density
Original language description
The size, complexity and dimensionality of data collections are ever increasing from the beginning of the computer era. Clustering methods, such as Growing Neural Gas (GNG) [10] that is based on unsupervised learning, is used to reveal structures and to reduce large amounts of raw data. The growth of computational complexity of such clustering method, caused by growing data dimensionality and the specific similarity measurement in a high-dimensional space, reduces the effectiveness of clustering method in many real applications. The growth of computational complexity can be partially solved using the parallel computation facilities, such as High Performance Computing (HPC) cluster with MPI. An effective parallel implementation of GNG is discussed in this paper, while the main focus is on minimizing of interprocess communication which depends on the number of neurons and edges among neurons in the neural network. A new algorithm of adding neurons depending on data density is proposed in the paper. (C) Springer Nature Switzerland AG 2018.
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
<a href="/en/project/LM2015070" target="_blank" >LM2015070: IT4Innovations National Supercomputing Center</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science. Volume 11127
ISBN
978-3-319-99953-1
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
10
Pages from-to
314-323
Publisher name
Springer
Place of publication
Cham
Event location
Olomouc
Event date
Sep 27, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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