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undergraduate thesis
Analiza teksta pomoću dubokih neuronskih mreža
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2017. urn:nbn:hr:168:835033
Bešić, Borna
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Bešić, B. (2017). Analiza teksta pomoću dubokih neuronskih mreža (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:835033

Bešić, Borna. "Analiza teksta pomoću dubokih neuronskih mreža." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2017. https://urn.nsk.hr/urn:nbn:hr:168:835033

Bešić, Borna. "Analiza teksta pomoću dubokih neuronskih mreža." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2017. https://urn.nsk.hr/urn:nbn:hr:168:835033

Bešić, B. (2017). 'Analiza teksta pomoću dubokih neuronskih mreža', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 27 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:835033

Bešić B. Analiza teksta pomoću dubokih neuronskih mreža [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2017 [cited 2024 December 27] Available at: https://urn.nsk.hr/urn:nbn:hr:168:835033

B. Bešić, "Analiza teksta pomoću dubokih neuronskih mreža", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2017. Available at: https://urn.nsk.hr/urn:nbn:hr:168:835033

Metadata
TitleAnaliza teksta pomoću dubokih neuronskih mreža
Title (english)Text Analysis Using Deep Neural Networks
AuthorBorna Bešić
MentorMarko Subašić (mentor)
Committee memberMarko Subašić (predsjednik povjerenstva)
Committee memberTomislav Pribanić (član povjerenstva)
Committee memberNikola Banić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2017-07-10, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Cilj ovog rada je opisati primjenu dubokih neuronskih mreža u klasifikaciji odsječaka teksta različite duljine s obzirom na jednu pripadajuću kategoriju. U prvom dijelu objašnjavaju se motivacija za korištenje modela u vektorskom prostoru te osnovni koncepti u pozadini Word2vec modela. Predstavljena je i detaljno analizirana korištena arhitektura konvolucijske neuronske mreže s naglaskom na inicijalizaciju težina, aktivacijsku funkciju, metodu optimizacije, funkciju pogreške te regularizaciju. U drugom dijelu opisani su korišteni skupovi podataka za treniranje modela neuronske mreže te su navedeni eksperimentalni rezultati dobiveni koristeći TensorFlow biblioteku u okviru programskog jezika Python.
Abstract (english)
The aim of this paper is to describe the use of deep neural networks in the single-label classification of various length texts. In the first part, the motivation for vector space models and the basic concepts behind the Word2vec model are explained. Then the used convolutional neural network architecture is analyzed in detail, with emphasis on weights initialization, activation function, optimization method, error function and regularization. In the second part, the datasets used to train the neural network model are described and experimental results are reported. The results were obtained using the TensorFlow library and the Python programming language.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:835033
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 19:03:24