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undergraduate thesis
Strojno učenje za sintezu sažetaka teksta
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. urn:nbn:hr:168:079743
Fatorić, Valentina
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Fatorić, V. (2018). Strojno učenje za sintezu sažetaka teksta (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:079743

Fatorić, Valentina. "Strojno učenje za sintezu sažetaka teksta." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:079743

Fatorić, Valentina. "Strojno učenje za sintezu sažetaka teksta." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:079743

Fatorić, V. (2018). 'Strojno učenje za sintezu sažetaka teksta', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 03 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:079743

Fatorić V. Strojno učenje za sintezu sažetaka teksta [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2018 [cited 2024 July 03] Available at: https://urn.nsk.hr/urn:nbn:hr:168:079743

V. Fatorić, "Strojno učenje za sintezu sažetaka teksta", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:168:079743

Metadata
TitleStrojno učenje za sintezu sažetaka teksta
Title (english)A Machine-learning Based Model for Text Summarization
AuthorValentina Fatorić
MentorVladimir Čeperić (mentor)
Committee memberVladimir Čeperić (predsjednik povjerenstva)
Committee memberPetra Bevandić (član povjerenstva)
Committee memberIvan Krešo (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
U ovom radu je opisan problem automatskog sažimanja teksta i dva različita pristupa tom problemu: ekstraktivno i apstraktivno sažimanje. Za ekstraktivno sažimanje su opisane različite metode koje se koriste za izdvajanje najbitnijih rečenica, a za apstraktivno je objašnjeno kako je strojevima omogućeno parafrazirati pomoću strojnog učenja i povratnih neuronskih mreža. Također, u ovom radu su objašnjene različite mjere ocjenjivanja generiranih sažetaka te je napravljena implementacija i usporedba rezultata oba pristupa.
Abstract (english)
This thesis describes the problem of automatic text summarization and two different approaches to this problem: extractive and abstractive summarization. For extractive summarization various methods are used for extracting the most important sentences and for abstractive summarization it is explained how machines can paraphrase by using machine learning and recurrent neural networks. In this thesis are also explained different evaluation measures for generated summaries and are made implementations and comparisons of the results of both approaches.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:079743
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 20:11:42