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master's thesis
Klasifikacija grafova korištenjem metoda strojnog učenja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:349963
Čačić, Ana
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Čačić, A. (2023). Klasifikacija grafova korištenjem metoda strojnog učenja (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:349963

Čačić, Ana. "Klasifikacija grafova korištenjem metoda strojnog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:349963

Čačić, Ana. "Klasifikacija grafova korištenjem metoda strojnog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:349963

Čačić, A. (2023). 'Klasifikacija grafova korištenjem metoda strojnog učenja', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 28 June 2024, https://urn.nsk.hr/urn:nbn:hr:168:349963

Čačić A. Klasifikacija grafova korištenjem metoda strojnog učenja [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 June 28] Available at: https://urn.nsk.hr/urn:nbn:hr:168:349963

A. Čačić, "Klasifikacija grafova korištenjem metoda strojnog učenja", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:349963

Metadata
TitleKlasifikacija grafova korištenjem metoda strojnog učenja
Title (english)Graph classification using machine learning techniques
AuthorAna Čačić
MentorLana Horvat Dmitrović (mentor)
Committee memberLana Horvat Dmitrović (predsjednik povjerenstva)
Committee memberAndrea Aglić Aljinović (član povjerenstva)
Committee memberJosipa Pina Milišić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-09-19, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Područje strojnog učenja temeljeno na grafovima je u posljednje vrijeme privuklo značajnu pozornost zbog svojeg potencijala rješavanja složenih realnih problema koji se mogu modelirati pomoću strukture grafa. Ovaj rad proučava problem klasifikacije grafova stvarajući novi skup podataka, koji predstavlja cestovne mreže europskih gradova, s ciljem da se modele istrenira klasificirati gradove u njihovu odgovarajuću državu. Problemu se pristupilo koristeći različite neuronske mreže grafova (GNN) kao što su GAT i GIN. Iako ne donosi finalni zaključak o izvedivosti ovog zadatka, ovaj rad služi kao početni korak u daljnjem istraživanju ovog problema.
Abstract (english)
The field of graph-based machine learning has recently gained a significant amount of attention due to its potential to solve complex real-world problems that can be modeled as graphs. This thesis delves into the problem of graph classification by creating a unique dataset that represents road networks across European cities and setting an objective to train models to classify these cities into their respective countries. This task was approached by using different graph neural networks (GNN), such as GAT and GIN. Although this thesis yields no definite conclusion regarding the feasibility of this task, it serves as an initial step in further research of this challenge.
Keywords
Keywords (english)
Languageenglish
URN:NBNurn:nbn:hr:168:349963
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 on2023-10-11 08:37:16