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master's thesis
Primjena modela dubokog učenja na analizu sentimenta izraza hrvatskoga jezika
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2014. urn:nbn:hr:168:760886
Biđin, Siniša
University of Zagreb
Faculty of Electrical Engineering and Computing

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Biđin, S. (2014). Primjena modela dubokog učenja na analizu sentimenta izraza hrvatskoga jezika (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:760886

Biđin, Siniša. "Primjena modela dubokog učenja na analizu sentimenta izraza hrvatskoga jezika." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2014. https://urn.nsk.hr/urn:nbn:hr:168:760886

Biđin, Siniša. "Primjena modela dubokog učenja na analizu sentimenta izraza hrvatskoga jezika." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2014. https://urn.nsk.hr/urn:nbn:hr:168:760886

Biđin, S. (2014). 'Primjena modela dubokog učenja na analizu sentimenta izraza hrvatskoga jezika', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 17 May 2024, https://urn.nsk.hr/urn:nbn:hr:168:760886

Biđin S. Primjena modela dubokog učenja na analizu sentimenta izraza hrvatskoga jezika [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2014 [cited 2024 May 17] Available at: https://urn.nsk.hr/urn:nbn:hr:168:760886

S. Biđin, "Primjena modela dubokog učenja na analizu sentimenta izraza hrvatskoga jezika", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2014. Available at: https://urn.nsk.hr/urn:nbn:hr:168:760886

Metadata
TitlePrimjena modela dubokog učenja na analizu sentimenta izraza hrvatskoga jezika
Title (english)Using Deep Learning for Sentiment Analysis of Expressions in Croatian Language
AuthorSiniša Biđin
MentorJan Šnajder (mentor)
Committee memberJan Šnajder (predsjednik povjerenstva)
Committee memberSiniša Šegvić (član povjerenstva)
Committee memberNikola Bogunović (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2014-07-07, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Uobičajeni postupci analize sentimenta temelje se na rječniku apriornog sentimenta. Problem predstavlja modeliranje sentimenta višerječnih izraza poput ``poprilično dobar'' ili ``nimalo loš'', ali i većih jezičnih jedinica. Opisan je i implementiran postupak učenja reprezentacija riječi prema metodi Colloberta i dr.~(2011) te postupak analize sentimenta višerječnih izraza hrvatskoga jezika modelom zasnovanom na rekurzivnoj neuronskoj mreži prema radu Sochera i dr.~(2012). Navedeni su rezultati učenja reprezentacija riječi na temelju dva različita korpusa i rezultati evaluacije modela za analizu sentimenta nad tri različita skupa za učenje.
Abstract (english)
Methods of sentiment analysis are usually based upon a sentiment-labeled lexicon. Problems arise when trying to model the sentiment of multi-word phrases such as ``pretty good'' or ``not bad'', but also of entire sentences. A word-representation training method based on Collobert et al.~(2011) is defined and implemented, as is a method for sentiment analysis of multi-word phrases written in Croatian using a model based on recursive neural networks according to Socher et al.~(2012). We state the results of word-representation training on two different corpora and the results of evaluating the sentiment analysis model on three different training sets.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:760886
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2018-02-06 07:53:31