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master's thesis
Sustav za automatizirani pregled literature
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:206769
Bacinger, Filip
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Bacinger, F. (2022). Sustav za automatizirani pregled literature (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:206769

Bacinger, Filip. "Sustav za automatizirani pregled literature." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:206769

Bacinger, Filip. "Sustav za automatizirani pregled literature." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:206769

Bacinger, F. (2022). 'Sustav za automatizirani pregled literature', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 26 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:206769

Bacinger F. Sustav za automatizirani pregled literature [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 December 26] Available at: https://urn.nsk.hr/urn:nbn:hr:168:206769

F. Bacinger, "Sustav za automatizirani pregled literature", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:206769

Metadata
TitleSustav za automatizirani pregled literature
Title (english)System for Automated Literature Review
AuthorFilip Bacinger
MentorIvica Botički (mentor)
Committee memberIvica Botički (predsjednik povjerenstva)
Committee memberTomislav Jagušt (član povjerenstva)
Committee memberDanijel Mlinarić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-14, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Sustavni pregled literature je važan oblik znanstvenog rada temeljen na pretraživanju velikog obujma literature, što čini proces vremenski intenzivnim. Ubrzavanje izrade pregleda literature pomoću automatiziranih sustava moglo bi doprinijeti bržem razvoju novog istraživanja. U radu je izrađena web-aplikacija koja omogućuje definiranje teme pregleda literature, automatsko pretraživanje izvora znanstvenih radova, automatsko označavanje radova (uz minimalan broj ručno označenih radova), pregled radova i izvoz rezultata u obliku dijagrama i svih pozitivno označenih radova. Za obradu teksta korištene su metode tokenizacije, uklanjanja stop-riječi, vađenja korijena (Lancaster algoritam) i računanja TF-IDF faktora. Obrađeni tekstovi koriste se u kombiniranom modelu strojnog učenja izrađenom od dvadeset i četiri (24) pojedinačna modela. Kombinirani model je podešen da prioritizira točnu klasifikaciju pozitivnih primjera i ostvaruje ukupnu točnost preko 80\%.
Abstract (english)
Systematic literature review is an important form of scientific work based on reviewing a large volume of literature, which makes the process time-intensive. Speeding up the creation of literature reviews with the help of automated systems could contribute to a faster development of new research. In this thesis, a web application is created which allows defining a subject for the literature review, automated querying of scientific article sources, automated article labelling (with a minimal number of manually labelled articles), viewing articles and exporting results in the form of a diagram and all positively labelled articles. Methods of tokenisation, stop-word removal, stemming (Lancaster algorithm) and calculating TF-IDF factors were used for text processing. Processed texts are used in a combined model of machine learning which comprises of twenty-four (24) individual models. The combined model is adjusted to prioritize correctly classifying positive articles and has an overall accuracy of over 80\%.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:206769
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 on2023-01-14 08:21:07