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master's thesis
Identifikacija sudionika u transkriptu razgovora između više osoba uporabom analize teksta
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. urn:nbn:hr:168:995361
Brajdić, Karlo
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Brajdić, K. (2019). Identifikacija sudionika u transkriptu razgovora između više osoba uporabom analize teksta (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:995361

Brajdić, Karlo. "Identifikacija sudionika u transkriptu razgovora između više osoba uporabom analize teksta." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:995361

Brajdić, Karlo. "Identifikacija sudionika u transkriptu razgovora između više osoba uporabom analize teksta." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:995361

Brajdić, K. (2019). 'Identifikacija sudionika u transkriptu razgovora između više osoba uporabom analize teksta', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 27 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:995361

Brajdić K. Identifikacija sudionika u transkriptu razgovora između više osoba uporabom analize teksta [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2019 [cited 2024 November 27] Available at: https://urn.nsk.hr/urn:nbn:hr:168:995361

K. Brajdić, "Identifikacija sudionika u transkriptu razgovora između više osoba uporabom analize teksta", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:168:995361

Metadata
TitleIdentifikacija sudionika u transkriptu razgovora između više osoba uporabom analize teksta
Title (english)Identifying Participants in Conversation Transcripts Involving Multiple People Using Text Analysis
AuthorKarlo Brajdić
MentorDamir Pintar (mentor)
Committee memberDamir Pintar (predsjednik povjerenstva)
Committee memberZoran Skočir (član povjerenstva)
Committee memberBoris Vrdoljak (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2019-07-09, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Identifikacija sudionika u transkriptu razgovora je problem koji je predstavljen kao uvod u veći problem, a to je rudarenje karaktera. Problem se rješava rezolucijom koreferentnosti, ali prijašnjim modelima je tekst u obliku dijaloga bio mana. Model rezolucije koreferentnosti zasnovan na parovima spominjanja se koristi u ovom radu, koji uz pomoć više tipova značajki grupira spominjanja u koreferentne lance. Sustav nakon toga povezuje entitete s tim lancima pomoću algoritma zasnovanog na glasanju. Ugniježđena unakrsna provjera i nekolicina modela su korištena pri evaluaciji sustava.
Abstract (english)
Character identification on multiparty conversation is a problem introduced as an intro to a bigger problem called character mining. Usually, the problem is solved using coreference resolution, but coreference resolution models at the time were struggling with data as dialogue. Mention-pair model is used for coreference resolution in this thesis, which links mentions in coreference chains. After that, the system links entities with chains using a voting scheme. Nested cross-validation and a number of models were used during the evaluation of the system.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:995361
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
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Created on2020-01-07 16:59:12