Data analysis with empirical probability functions as a data mining method: Employing CF-miner and pattern difference quantifiers
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61384399%3A31140%2F18%3A00052670" target="_blank" >RIV/61384399:31140/18:00052670 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21260/18:00329427
Result on the web
<a href="https://ieeexplore.ieee.org/document/8402674" target="_blank" >https://ieeexplore.ieee.org/document/8402674</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SCSP.2018.8402674" target="_blank" >10.1109/SCSP.2018.8402674</a>
Alternative languages
Result language
angličtina
Original language name
Data analysis with empirical probability functions as a data mining method: Employing CF-miner and pattern difference quantifiers
Original language description
Main topics of the document: data analysis; data mining; difference histogram; histogram analysis; pattern difference; GUHA; LISp-Miner
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
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
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
Smart Cities Symposium Prague (SCSP), 2018
ISBN
978-1-5386-5017-2
ISSN
—
e-ISSN
—
Number of pages
6
Pages from-to
"nestrankovano"
Publisher name
IEEE
Place of publication
Praha
Event location
Praha
Event date
May 24, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000443451800029