DocumentCode
3164425
Title
Intelligent granulation of machine-generated data
Author
Slezak, Dominik ; Kowalski, Matthieu
Author_Institution
Inst. of Math., Univ. of Warsaw, Warsaw, Poland
fYear
2013
fDate
24-28 June 2013
Firstpage
68
Lastpage
73
Abstract
We discuss how the specifics of data granulation methodology can influence Infobright´s database system performance. We put together our two previous research paths related to machine-generated data sets, namely, dynamic reorganization of data during load and efficient handling of alphanumeric columns with compound values. We emphasize the role of domain knowledge while tuning data granulation processes.
Keywords
data handling; granular computing; inference mechanisms; Infobright database system; alphanumeric columns; compound values; data granulation methodology; dynamic reorganization; granulation processes; intelligent granulation; machine generated data; Approximation methods; Compounds; Data mining; Database systems; Dictionaries; Rough sets; Analytic Databases; Compound Values; Domain Knowledge; Outliers; Stream Clustering;
fLanguage
English
Publisher
ieee
Conference_Titel
IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS), 2013 Joint
Conference_Location
Edmonton, AB
Type
conf
DOI
10.1109/IFSA-NAFIPS.2013.6608377
Filename
6608377
Link To Document