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Latest Academic Works

Representing and exploiting benchmarking data for optimisation and learning

Author(s): Ana Kostovska (Author), Panče Panov (Supervisor), Sašo Džeroski (Co-Supervisor), Tome Eftimov (Co-Supervisor)

Year: 2025

Type: Doctoral dissertation

The rapid advancements in Machine Learning (ML) and Black-Box Optimization (BBO) have led to an increased reliance on benchmarking data for evaluating and comparing algorithms across diverse domain tasks. However, the effective exploitation of this data is hindered by challenges such as syntactic variability, semantic ambiguity, and lack of standardization. …

Machine learning methodology for automatic metadata assignment in cultural heritage archives

Author(s): Luis Rei (Author), Dunja Mladenić (Supervisor)

Year: 2024

Type: Doctoral dissertation

This thesis introduces a novel machine learning methodology for automatically assigning metadata to digitized artifacts in cultural heritage. Cultural heritage is an example of a domain that requires expert labeling, with few pre-existing labeled datasets and where simply getting more labeled data is challenging. The societal importance of cultural heritage …

Information spreading barriers in news

Author(s): Abdul Sittar (Author), Dunja Mladenić (Supervisor)

Year: 2024

Type: Doctoral dissertation

News spreads in many patterns, structures, and dynamics that change throughout time. For a variety of reasons, certain news is only covered in a particular area. Language, economy, geography, politics, time zone, and culture are just a few of the many barriers that prevent news from reaching a larger audience. …

An automated vulnerability detection for website security

Author(s): Primož Cigoj (Author), Borka Jerman Blažič (Supervisor)

Year: 2021

Type: Doctoral dissertation

Although large research efforts on web application security have been invested for more than a decade, the security of web applications is still a challenging problem. The main focus of the cybersecurity community has been to make operating systems and communication networks more secure and harder for attackers to penetrate. …