bibtype	K - Conference Paper (Czech conference)
ARLID	0411033
utime	20240103182257.0
mtime	20060210235959.9
ISBN	80-248-0229-5
title (primary) (eng)	Application of finite mixtures to text document classification
publisher	place Ostrava name VŠB pub_time 2003
specification	page_count 10 s.
serial	title Znalosti 2003. Sborník příspěvků 2. ročníku konference page_num 23-32 editor name1 Svátek name2 V.
keyword	text classification
keyword	mixture model
author (primary)	ARLID cav_un_auth*0101171 name1 Novovičová name2 Jana institution UTIA-B fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author	ARLID cav_un_auth*0101155 name1 Malík name2 Antonín institution UTIA-B fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
COSATI	09K
COSATI	12B
cas_special	project project_id IAA2075302 agency GA AV ČR ARLID cav_un_auth*0001801 project project_id KSK1019101 agency GA AV ČR ARLID cav_un_auth*0000219 research CEZ:AV0Z1075907 abstract (eng) Finite mixture modelling of class-conditional distributions is a standard method in a statistical pattern recognition. We proposed to use the mixture of multinomial distributions as a model for class-conditional distribution for text document classification task. The vector document representations using a bag-of-words or a unigram approach are employed. Experimental comparison of the proposed model and the standard models was performed using Reuters-21578 database. action ARLID cav_un_auth*0213006 name Znalosti 2003 /2./ place Ostrava country CZ dates 19.02.2003-21.02.2003 RIV BB department RO permalink http://hdl.handle.net/11104/0131120 ID_orig UTIA-B 20030020 arlyear 2003 mrcbU10 2003 mrcbU10 Ostrava VŠB mrcbU12 80-248-0229-5 mrcbU63 Znalosti 2003. Sborník příspěvků 2. ročníku konference 23 32 mrcbU67 Svátek V. 340