Graph construction based on local representativeness
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F17%3A10238662" target="_blank" >RIV/61989100:27240/17:10238662 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-319-62389-4_54" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-62389-4_54</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-62389-4_54" target="_blank" >10.1007/978-3-319-62389-4_54</a>
Alternative languages
Result language
angličtina
Original language name
Graph construction based on local representativeness
Original language description
Graph construction is a known method of transferring the problem of classic vector data mining to network analysis. The advantage of networks is that the data are extended by links between certain (similar) pairs of data objects, so relationships in the data can then be visualized in a natural way. In this area, there are many algorithms, often with significantly different results. A common problem for all algorithms is to find relationships in data so as to preserve the characteristics related to the internal structure of the data. We present a method of graph construction based on a network reduction algorithm, which is found on analysis of the representativeness of the nodes of the network. It was verified experimentally that this algorithm preserves structural characteristics of the network during the reduction. This approach serves as the basis for our method which does not require any default parameters. In our experiments, we show the comparison of our graph construction method with one well-known method based on the most commonly used approach. © 2017, Springer International Publishing AG.
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/NV16-31852A" target="_blank" >NV16-31852A: Prediction for reoperation in patients with THA and TKA based on immunogenetic signature: development of risk calculator for routine clinical practice</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
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
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Volume 10392
ISBN
978-3-319-62388-7
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
12
Pages from-to
654-665
Publisher name
Springer
Place of publication
Cham
Event location
Hongkong
Event date
Aug 3, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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