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Statements

Subject Item
n2:RIV%2F00216305%3A26220%2F11%3APU91444%21RIV12-MSM-26220___
rdf:type
n8:Vysledek skos:Concept
dcterms:description
Since the amount of information stored in the form of electronic text documents has been rapidly growing over the past few years, there is an increasing demand for tools enabling to automatically analyze these documents and benefit from their emotional content. This paper describes experiments concerned with an automatic analysis of emotions in Czech text. The selected method has some characteristics of hybrid approach to emotion recognition as it is not only based on machine learning but also utilizes a lexical database and derived domain dictionaries. A fundamental part of machine learning methods is training data set and therefore the creation of an emotional corpus is described as well. The purpose of this paper is to introduce implemented system, present and evaluate achieved results of classification of text documents into defined emotion classes. Since the amount of information stored in the form of electronic text documents has been rapidly growing over the past few years, there is an increasing demand for tools enabling to automatically analyze these documents and benefit from their emotional content. This paper describes experiments concerned with an automatic analysis of emotions in Czech text. The selected method has some characteristics of hybrid approach to emotion recognition as it is not only based on machine learning but also utilizes a lexical database and derived domain dictionaries. A fundamental part of machine learning methods is training data set and therefore the creation of an emotional corpus is described as well. The purpose of this paper is to introduce implemented system, present and evaluate achieved results of classification of text documents into defined emotion classes.
dcterms:title
Identifying Expression of Emotions in Czech Text Using Semantic Relations for Dimension Reduction Identifying Expression of Emotions in Czech Text Using Semantic Relations for Dimension Reduction
skos:prefLabel
Identifying Expression of Emotions in Czech Text Using Semantic Relations for Dimension Reduction Identifying Expression of Emotions in Czech Text Using Semantic Relations for Dimension Reduction
skos:notation
RIV/00216305:26220/11:PU91444!RIV12-MSM-26220___
n8:predkladatel
n13:orjk%3A26220
n3:aktivita
n19:P n19:Z
n3:aktivity
P(FR-TI2/679), Z(MSM0021630513)
n3:cisloPeriodika
1
n3:dodaniDat
n7:2012
n3:domaciTvurceVysledku
n10:3203107 n10:2629291
n3:druhVysledku
n18:J
n3:duvernostUdaju
n5:S
n3:entitaPredkladatele
n15:predkladatel
n3:idSjednocenehoVysledku
203437
n3:idVysledku
RIV/00216305:26220/11:PU91444
n3:jazykVysledku
n17:eng
n3:klicovaSlova
text processing, emotions, semantics, artificial inteligency
n3:klicoveSlovo
n6:artificial%20inteligency n6:semantics n6:emotions n6:text%20processing
n3:kodStatuVydavatele
CZ - Česká republika
n3:kontrolniKodProRIV
[2BD079B72CCB]
n3:nazevZdroje
Elektrorevue - Internetový časopis (http://www.elektrorevue.cz)
n3:obor
n9:BD
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n20:FR-TI2%2F679
n3:rokUplatneniVysledku
n7:2011
n3:svazekPeriodika
2011
n3:tvurceVysledku
Burget, Radim Červenec, Radek
n3:zamer
n16:MSM0021630513
s:issn
1213-1539
s:numberOfPages
7
n11:organizacniJednotka
26220