bibtype J - Journal Article
ARLID 0410441
utime 20240103182214.3
mtime 20060210235959.9
title (primary) (eng) Probabilistic information retrieval from census data based on distribution mixtures
specification
page_count 7 s.
serial
ARLID cav_un_epca*0297072
ISSN 0572-3043
title Acta Oeconomica Pragensia
volume_id 8
volume 2 (2000)
page_num 41-47
author (primary)
ARLID cav_un_auth*0101091
name1 Grim
name2 Jiří
institution UTIA-B
full_dept Department of Pattern Recognition
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101182
name1 Pudil
name2 Pavel
institution UTIA-B
full_dept Department of Pattern Recognition
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101197
name1 Somol
name2 Petr
institution UTIA-B
full_dept Department of Pattern Recognition
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
COSATI 09K
cas_special
project
project_id VS96063
agency MŠMT
country CZ
ARLID cav_un_auth*0025066
project
project_id IAA2075703
agency GA AV
country CZ
ARLID cav_un_auth*0218731
project
project_id KSK1075601
agency GA AV
country CZ
ARLID cav_un_auth*0027435
research AV0Z1075907
abstract (eng) The possibility of interactive presentation of statistical properties of large and/or confidential databases by means of probabilistic models is based on the probabilistic expert system PES. The probabilistic model can be estimated by means of EM algorithm in the form of a finite distribution mixture to be used as a knowledge base of the probabilistic expert system PES. The final software product can reproduce the properties of the original database without any further access to the original data.
RIV BB
department RO
permalink http://hdl.handle.net/11104/0130530
ID_orig UTIA-B 20000157
arlyear 2000
mrcbU63 cav_un_epca*0297072 Acta Oeconomica Pragensia 0572-3043 Roč. 8 č. 2 2000 41 47