A proposal of hierarchical vertex clustering based on the Gosper curve
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10238694" target="_blank" >RIV/61989100:27240/17:10238694 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27740/17:10238694
Result on the web
<a href="http://dx.doi.org/10.1109/SMC.2016.7844311" target="_blank" >http://dx.doi.org/10.1109/SMC.2016.7844311</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SMC.2016.7844311" target="_blank" >10.1109/SMC.2016.7844311</a>
Alternative languages
Result language
angličtina
Original language name
A proposal of hierarchical vertex clustering based on the Gosper curve
Original language description
Space-filling curves (SFCs) are straightforward and efficient methods for a sparse space clustering. They are utilized in research areas like classification, computer vision, computer graphics and/or machine learning. Most of the SFCs are based on a regular orthogonal grid. Generally, a hierarchical properties of Quad-trees (2D) or Octrees (n-dimensional) are utilized for a vertex hashing. However, the regular hexagonal grid is applicable for 2D tiling as well. The hexagonal shape is principally not a reptile, so the construction of hexagonal SFCs or a query structure is still a complex task. The Gosper curve (Flowsnake) is a self similar fractal that groups the hexagons to a composite called the Gosper island. This paper proposes a novel method constructing a Gosper-like space-filling curve of 2D vertices. The final algorithm is tested on several datasets and the results are discussed.
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
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Intelligent data analysis and applications: proceedings of the Third Euro-China Conference on Intelligent Data Analysis and Applications, ECC 2016
ISBN
978-3-319-48498-3
ISSN
2194-5357
e-ISSN
neuvedeno
Number of pages
6
Pages from-to
632-637
Publisher name
Springer
Place of publication
Cham
Event location
Fu-čou
Event date
Nov 7, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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