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master's thesis
Klasifikator riječi za hrvatski morfološki leksikon
2017. urn:nbn:hr:166:157189
Škugor, Franka
University of Split
Faculty of Science
Department of Informatics

Cite this document

Škugor, F. (2017). Klasifikator riječi za hrvatski morfološki leksikon (Master's thesis). Split: University of Split, Faculty of Science. Retrieved from https://urn.nsk.hr/urn:nbn:hr:166:157189

Škugor, Franka. "Klasifikator riječi za hrvatski morfološki leksikon." Master's thesis, University of Split, Faculty of Science, 2017. https://urn.nsk.hr/urn:nbn:hr:166:157189

Škugor, Franka. "Klasifikator riječi za hrvatski morfološki leksikon." Master's thesis, University of Split, Faculty of Science, 2017. https://urn.nsk.hr/urn:nbn:hr:166:157189

Škugor, F. (2017). 'Klasifikator riječi za hrvatski morfološki leksikon', Master's thesis, University of Split, Faculty of Science, accessed 11 December 2024, https://urn.nsk.hr/urn:nbn:hr:166:157189

Škugor F. Klasifikator riječi za hrvatski morfološki leksikon [Master's thesis]. Split: University of Split, Faculty of Science; 2017 [cited 2024 December 11] Available at: https://urn.nsk.hr/urn:nbn:hr:166:157189

F. Škugor, "Klasifikator riječi za hrvatski morfološki leksikon", Master's thesis, University of Split, Faculty of Science, Split, 2017. Available at: https://urn.nsk.hr/urn:nbn:hr:166:157189

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Metadata
TitleKlasifikator riječi za hrvatski morfološki leksikon
Title (english)Word classificator for Croatian Morphological Lexicon
AuthorFranka Škugor
MentorBranko Žitko (mentor)
Committee memberBranko Žitko (predsjednik povjerenstva)
Committee memberAni Grubišić (član povjerenstva)
Committee memberDivna Krpan (član povjerenstva)
GranterUniversity of Split
Faculty of Science
(Department of Informatics)
Split
Defense date and country2017-12-21, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Morfološki bogati jezici izražavaju višestruke razine gramatičkih informacija već na razini riječi. U ovom diplomskom radu, glavna tematika je klasifikacija teksta i evaluacija. Proveden je eksperiment proširivanja hrvatskog morfološkog leksikona (HML) sa nepoznatim riječima. Klasifikacija je postignuta na dva načina: metodom sufiksnog stabla i statističkom metodom strojnog učenja - maksimalnom entropijom. Nakon točnog klasificiranja riječi jednom od metoda, generiranje svih oblika riječi je izvedeno metodom sufiksnog stabla. Rezultati klasificiranja i generiranja oblika su vrednovani uz pomoć tri najkorištenije mjere u području klasifikacije teksta: preciznost, opoziv i F1 mjera.
Abstract (english)
Morphologically rich languages (MRLs) express multiple levels of information already at the word level. The main terms in this master thesis are classification and evaluation. An experiment of expanding croatian morphological lexicon (HML) with unknown words was conducted. Classification was done by two different approaches: suffix trie method and statistical approach with machine learning - maximum entropy. After correctly classifying word using one of the classifiers, generation of all word forms was done by suffix trie method. Results were collected and evaluated by three most used measures in text classification: precision, recall and F1 measure.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:166:157189
Study programmeTitle: Computer Science; specializations in: major in teaching
Course: major in teaching
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra edukacije informatike (magistar/magistra edukacije informatike)
Type of resourceText
File originBorn digital
Access conditionsAccess restricted to students and staff of home institution
Terms of useLicence In copyright icon
Created on2018-03-16 18:01:48