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undergraduate thesis
Primjena modela dubokog učenja za otkrivanje stavova u korisničkim komentarima
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2016. urn:nbn:hr:168:883531
Freškura, Bartol
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Freškura, B. (2016). Primjena modela dubokog učenja za otkrivanje stavova u korisničkim komentarima (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:883531

Freškura, Bartol. "Primjena modela dubokog učenja za otkrivanje stavova u korisničkim komentarima." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2016. https://urn.nsk.hr/urn:nbn:hr:168:883531

Freškura, Bartol. "Primjena modela dubokog učenja za otkrivanje stavova u korisničkim komentarima." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2016. https://urn.nsk.hr/urn:nbn:hr:168:883531

Freškura, B. (2016). 'Primjena modela dubokog učenja za otkrivanje stavova u korisničkim komentarima', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 18 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:883531

Freškura B. Primjena modela dubokog učenja za otkrivanje stavova u korisničkim komentarima [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2016 [cited 2024 November 18] Available at: https://urn.nsk.hr/urn:nbn:hr:168:883531

B. Freškura, "Primjena modela dubokog učenja za otkrivanje stavova u korisničkim komentarima", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2016. Available at: https://urn.nsk.hr/urn:nbn:hr:168:883531

Metadata
TitlePrimjena modela dubokog učenja za otkrivanje stavova u korisničkim komentarima
Title (english)Application of Deep Learning for Stance Detection in User Comments
AuthorBartol Freškura
MentorJan Šnajder (mentor)
Committee memberJan Šnajder (predsjednik povjerenstva)
Committee memberDomagoj Alagić (član povjerenstva)
Committee memberMartin Tutek (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2016-07-11, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Duboko učenje je relativno nova grana strojnog učenja koja se temelji na teoriji neuronskih mreža. Pomoću naprednih arhitektura dubokih neuronskih mreža danas se pokušavaju riješiti poznati problemi u području obrade prirodnog jezika kao što su analiza stavova i sentimenta. U sklopu završnog rada napravljene su dvije poznate konfiguracije povratnih neuronskih mreža LSTM i GRU pomoću programa Tensor- flow. Provedeni su razni eksperimenti u kojima se traže optimalni parametri povratnih neuronskih mreža s ciljem točne klasifikacije stavova u korisničkim komentarima iz skupova podataka na hrvatskom i engleskom jeziku.
Abstract (english)
Deep learning is a relatively new branch of machine learning based on the theory of neural networks. Using the advanced deep neural network architectures, today’s well- known natural language processing problems like sentiment and opinion mining are being solved. Two widely used configurations of recurrent neural networks were cre- ated with the Tensorflow software: LSTM and GRU. Many different experiments were conducted in which the focus was on finding the optimal parameters of the recurrent neural networks, which would yield in correct stance classification of user comments from the Croatian and English datasets.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:883531
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2018-02-06 08:46:55