prikaz prve stranice dokumenta Automatska detekcija nastavnih koncepata iz tekstova zadataka uporabom metoda dubinske analize teksta
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undergraduate thesis
Automatska detekcija nastavnih koncepata iz tekstova zadataka uporabom metoda dubinske analize teksta
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. urn:nbn:hr:168:310264
Begušić, Domagoj
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Begušić, D. (2018). Automatska detekcija nastavnih koncepata iz tekstova zadataka uporabom metoda dubinske analize teksta (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:310264

Begušić, Domagoj. "Automatska detekcija nastavnih koncepata iz tekstova zadataka uporabom metoda dubinske analize teksta." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:310264

Begušić, Domagoj. "Automatska detekcija nastavnih koncepata iz tekstova zadataka uporabom metoda dubinske analize teksta." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:310264

Begušić, D. (2018). 'Automatska detekcija nastavnih koncepata iz tekstova zadataka uporabom metoda dubinske analize teksta', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 28 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:310264

Begušić D. Automatska detekcija nastavnih koncepata iz tekstova zadataka uporabom metoda dubinske analize teksta [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2018 [cited 2024 July 28] Available at: https://urn.nsk.hr/urn:nbn:hr:168:310264

D. Begušić, "Automatska detekcija nastavnih koncepata iz tekstova zadataka uporabom metoda dubinske analize teksta", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:168:310264

Metadata
TitleAutomatska detekcija nastavnih koncepata iz tekstova zadataka uporabom metoda dubinske analize teksta
Title (english)Automatic discovery of conceptual concepts from test questions using the method of deep text analysis
AuthorDomagoj Begušić
MentorDamir Pintar (mentor)
Committee memberDamir Pintar (predsjednik povjerenstva)
Committee memberMihaela Vranić (član povjerenstva)
Committee memberLuka Humski (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
Sustavi za digitalno učenje generiraju ogromne količine podataka iz kojih se dubinskom analizom mogu izvući informacije koje nisu dostupne jednostavnim pretraživanjem. Primjenom programskog okruženja Python razvijen je sustav za automatsku klasifikaciju zadataka predmeta Osnove elektrotehnike Fakulteta elektrotehnike i računarstva u Zagrebu po prethodno dodijeljenim glavnim i sporednim konceptima. Objašnjene su korištene metode predobrade i vektorizacije zadataka. Klasifikacija je izvedena po glavnim i sporednim konceptima odvojeno, združenim glavnim i sporednim konceptima i hijerarhijski. Izgrađeno je pet različitih klasifikatora te su komentirani dobiveni rezultati za svaki slučaj klasifikacije.
Abstract (english)
Digital learning systems generate huge amounts of data from which information that is not accessible by simple search can be collected by applying data mining methods. Using the Python program environment, an automated classification system for the exam questions of Electrical Engineering course at the Faculty of Electrical Engineering and Computing in Zagreb was developed over previously assigned primary and secondary concepts. Used pre-processing and vectorization methods are explained. Classification is performed by primary and secondary concepts separately, joined primary and secondary concepts, and hierarchically. Five different classifiers were constructed and the results for each case were commented.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:310264
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 18:57:17