prikaz prve stranice dokumenta Modeli dubokog učenja za analizu korisničkih komentara na društvenim mrežama
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master's thesis
Modeli dubokog učenja za analizu korisničkih komentara na društvenim mrežama
2017. urn:nbn:hr:168:068873
Marinković, Tomislav
University of Zagreb
Faculty of Electrical Engineering and Computing

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Marinković, T. (2017). Modeli dubokog učenja za analizu korisničkih komentara na društvenim mrežama (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:068873

Marinković, Tomislav. "Modeli dubokog učenja za analizu korisničkih komentara na društvenim mrežama." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2017. https://urn.nsk.hr/urn:nbn:hr:168:068873

Marinković, Tomislav. "Modeli dubokog učenja za analizu korisničkih komentara na društvenim mrežama." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2017. https://urn.nsk.hr/urn:nbn:hr:168:068873

Marinković, T. (2017). 'Modeli dubokog učenja za analizu korisničkih komentara na društvenim mrežama', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 14 April 2025, https://urn.nsk.hr/urn:nbn:hr:168:068873

Marinković T. Modeli dubokog učenja za analizu korisničkih komentara na društvenim mrežama [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2017 [cited 2025 April 14] Available at: https://urn.nsk.hr/urn:nbn:hr:168:068873

T. Marinković, "Modeli dubokog učenja za analizu korisničkih komentara na društvenim mrežama", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2017. Available at: https://urn.nsk.hr/urn:nbn:hr:168:068873

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Metadata
TitleModeli dubokog učenja za analizu korisničkih komentara na društvenim mrežama
Title (english)Deep Learning Models for the Analysis of User Comments on Social Networks
AuthorTomislav Marinković
MentorJan Šnajder (mentor)
Committee memberJan Šnajder (predsjednik povjerenstva)
Committee memberAnte Đerek (član povjerenstva)
Committee memberAlan Jović (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2017-07-13, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U zadnje vrijeme duboko učenje polako uzima maha i postavlja se kao način za izradu umjetne inteligencije. Jedan od važnih segmenta umjetne inteligencije je razumjevanje prirodnog jezika. U ovom radu dan je pregled nekih algoritama s kojim je moguće odrediti sentiment, emociju, temu i govorni čin iz komentara sa Facebook stranica hrvatskih telekomunikacijskih kompanija.
Abstract (english)
In recent years deep learning is starting to take off in the world of artificial intelligence, and is starting to be the default approach of machine learning. One of the most important parts of artificial intelligence is understanding natural language. In this thesis, some promising algorithms are looked into. Those algorithms can determine sentiment, emotion, topic, and speech act of users comments posted on Facebook.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:068873
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
Access conditionsClosed access
Terms of useLicence In copyright icon
Public note
Created on2019-03-13 22:40:51
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