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master's thesis
Metode analize teksta u sustavima za potporu korisnicima
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. urn:nbn:hr:168:435401
Šušak, Ante
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Šušak, A. (2020). Metode analize teksta u sustavima za potporu korisnicima (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:435401

Šušak, Ante. "Metode analize teksta u sustavima za potporu korisnicima." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:435401

Šušak, Ante. "Metode analize teksta u sustavima za potporu korisnicima." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:435401

Šušak, A. (2020). 'Metode analize teksta u sustavima za potporu korisnicima', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 27 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:435401

Šušak A. Metode analize teksta u sustavima za potporu korisnicima [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 December 27] Available at: https://urn.nsk.hr/urn:nbn:hr:168:435401

A. Šušak, "Metode analize teksta u sustavima za potporu korisnicima", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:435401

Metadata
TitleMetode analize teksta u sustavima za potporu korisnicima
Title (english)Text Analysis Methods for Customer Support Systems
AuthorAnte Šušak
MentorSven Lončarić (mentor)
Committee memberSven Lončarić (predsjednik povjerenstva)
Committee memberMarko Subašić (član povjerenstva)
Committee memberTomislav Petković (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-07-08, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Metode analize teksta imaju važnu ulogu u rješavanju problema detekcije semantički jednakih pitanja, čije rješavanje ima izravnu primjenu u sustavima za potporu korisnicima. U ovom radu taj se problem rješava uz pomoć pristupa zasnovanom na strojnom učenju, gdje se kao značajke koriste rezultati različitih metoda analize teksta. Kod evaluacije sustava razmatrano je više modela, a najboljim se pokazao model koji koristi gradient boosting. Opisana je i jednostavna web aplikacija koja koristi implementirani model.
Abstract (english)
Text analysis methods play an important role in solving the problem of detecting semantically equal questions, the solution of which has a direct application in customer support systems. In this thesis, this problem is solved with the help of a machine learning-based approach, where the results of different text analysis methods are used as features. When evaluating the system, several models were considered, and the model using gradient boosting proved to be the best. A simple web application using the implemented model is also described.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:435401
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
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Created on2023-01-13 10:49:20