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undergraduate thesis
Analiza sentimenta iz korisničkih recenzija ugostiteljskih objekata
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. urn:nbn:hr:168:318602
Kerčmar, Roman
University of Zagreb
Faculty of Electrical Engineering and Computing

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Kerčmar, R. (2018). Analiza sentimenta iz korisničkih recenzija ugostiteljskih objekata (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:318602

Kerčmar, Roman. "Analiza sentimenta iz korisničkih recenzija ugostiteljskih objekata." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:318602

Kerčmar, Roman. "Analiza sentimenta iz korisničkih recenzija ugostiteljskih objekata." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:318602

Kerčmar, R. (2018). 'Analiza sentimenta iz korisničkih recenzija ugostiteljskih objekata', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 19 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:318602

Kerčmar R. Analiza sentimenta iz korisničkih recenzija ugostiteljskih objekata [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2018 [cited 2024 December 19] Available at: https://urn.nsk.hr/urn:nbn:hr:168:318602

R. Kerčmar, "Analiza sentimenta iz korisničkih recenzija ugostiteljskih objekata", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:168:318602

Metadata
TitleAnaliza sentimenta iz korisničkih recenzija ugostiteljskih objekata
Title (english)Sentiment Analysis from Customer Reviews of Hospitality and Catering Businesses
AuthorRoman Kerčmar
MentorJan Šnajder (mentor)
Committee memberJan Šnajder (predsjednik povjerenstva)
Committee memberMladen Karan (član povjerenstva)
Committee memberDomagoj Alagić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2018-07-13, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Analiza sentimenta iz korisničkih recenzija teži predvidjeti korisničku ocjenu isključivo na temelju teksta. Ispitane su dvije arhitekture neuronskih mreža, Konvolucijske i dvosmjerne povratne mreže. Učene su kao regresijski i kao klasifikacijski modeli. Dvosmjerne povratne mreže u kombinaciji s LSTM ćelijom pokazale su se najbolje i prema Pearsonovom koeficijentu korelacije (0.842) i prema točnosti (0.65).
Abstract (english)
Sentiment analysis from customer reviews aims to predict user grade by looking only at the text of the review. We examine two architectures of neural networks, convolutional and bidirectional neural networks. Models are trained as regression models and as classifiers. Bidirectional neural networks with LSTM as the base cell have shown to be the best with highest Pearson's correlation coefficient (0.842) and accuracy (0.65).
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:318602
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 on2019-03-13 21:30:37