Statistics of RUP

Bibliography of the person, including all types of documents, not only theses.

MSc theses (11)

1. Sead Hrustanović: Recognition of eudaemonic and hedonic qualities from song lyrics
2. Eva Puc: Filmski priporočilni sistem – psihološki konstrukti ali ocena všečnosti in filmski žanr
3. Đorđe Klisura: Automated pipeline for binary classification of high-dimensional biomedical data
4. Uroš Sergaš: Tribalizem in lažne novice: opisni in napovedni modeli vpliva prepričanj na zaupanje novicam
5. Arsen Matej Golubovikj: Imputing missing answers in the World Values Survey
6. Mateja Jovanović: Predicting the gullibility of users from their online behaviour
7. Aleksandar Avdalović: Prevod naključnih gozdov v imperativne programe brez zanke za namen formalnega preverjanja
8. Gregor Grbec: Rangiranje nogometašev z uporabo večnivojskega modeliranja
9. Elena Spirova: Music and myth
10. Špela Čučko: Sofisticiranost ocenjevanja glasbe in vpliv razlage na priporočila
11. Valentina Pucer: Razložljiva umetna inteligenca pri napovedovanju verjetnosti neplačila v bančništvu

BSc theses (14)

1. Sebastijan Peruško: Uporaba razpoloženja objav na omrežju Twitter za napovedovanje vrednosti delnice TSLA
2. Igor Saveski: Napovedovanje in izbira strategij za izboljšanje napovedi športnih stavnic
3. Simeon Stanić: Povečanje dobička z nakupom in prodajo kriptožetonov na podlagi priporočil iz usposobljenega modela
4. Riste Micev: Izvedba in ocenjevanje uporabniško usmerjenega sistema za priporočanje filmov
5. Jana Ristovska: Spodbujevalno učenje s pomočjo človeka na primeru igre Flappy Bird
6. Nadeen Al Hawamdeh: Analiza pomena značilk za napoved ocen filmov
7. Mirko Dugajlić: Prediction of song qualities from audio and lyrics
8. Anja Pijak: Predicting the development of user preferences from childhood to adulthood in the movie and cartoon domains with machine learning
9. Lirak Kerleshi: Which explanation is better for helping the end user distinguish fake news from real news?
10. Kristina Ðukić: Prediction of emotional responses and song preferences from user and song characteristics
11. Ana Nikolić, Ana Nikolić: Designing the ideal political identity questionnaire using machine learning and ideology scales
12. Una Novaković: Prediction of user preferences for dog breeds from user personality
13. Elena Nenadović: Prediction of AI-generated art style preferences from film preferences
14. Tamara Mikač: Analiza vpliva tehnologije na kakovost spanja

Other documents (25)

1. Mehdi Elahi, Farshad B. Moghaddam, Reza Hosseini, Mohammad Hossein Rimaz, Nabil El Ioini, Marko Tkalčič, Christoph Trattner, Tammam Tillo: Recommending videos in cold start with automatic visual tags
2. Shabnam Najafian, Amra Delić, Marko Tkalčič, Nava Tintarev: Factors influencing privacy concern for explanations of group recommendation
3. Bruce Ferwerda, Emily Yang, Markus Schedl, Marko Tkalčič: Personality and taxonomy preferences, and the influence of category choice on the user experience for music streaming services
4. Mohammad Hossein Rimaz, Mehdi Elahi, Farshad Bakhshandegan Moghadam, Christoph Trattner, Reza Hosseini, Marko Tkalčič: Exploring the power of visual features for the recommendation of movies
5. Mark P. Graus, Bruce Ferwerda, Marko Tkalčič, Panagiotis Germanakos: A summary of the third workshop on theory-informed user modeling for tailoring and personalizing interfaces
6. Bruce Ferwerda, Marko Tkalčič: Exploring online music listening behaviors of musically sophisticated users
7. Mark P. Graus, Bruce Ferwerda, Marko Tkalčič, Panagiotis Germanakos: Third workshop on theory-informed user modeling for tailoring and personalizing interfaces (HUMANIZE)
8. Marko Tkalčič: Complementing behavioural modeling with cognitive modeling for better recommendations
9. Bruce Ferwerda, Marko Tkalčič: Predicting users' personality from instagram pictures
10. Marko Tkalčič: Emotions and personality in recommender systems
11. Mark P. Graus, Bruce Ferwerda, Marko Tkalčič, Panagiotis Germanakos: Fourth HUMANIZE workshop on transparency and explainability in adaptive systems through user modeling grounded in psychological theory
12. Bruce Ferwerda, Marko Tkalčič: Exploring the prediction of personality traits from drug consumption profiles
13. Francesco Barile, Francesco Ricci, Marko Tkalčič, Bernardo Magnini, Roberto Zanoli, Alberto Lavelli, Manuela Speranza: A news recommender system for media monitoring
14. Farshad B. Moghaddam, Mehdi Elahi, Reza Hosseini, Christoph Trattner, Marko Tkalčič: Predicting movie popularity and ratings with visual features
15. Marko Tkalčič, Maria Soledad Pera: ACM RecSys'19 late-breaking results (posters)
16. Francesco Barile, Francesco Ricci, Marko Tkalčič, Bernardo Magnini, Roberto Zanoli, Alberto Lavelli, Manuela Speranza: Media monitoring using news recommenders
17. Marko Tkalčič, Maria Soledad Pera: Preface
18. Marko Tkalčič, Markus Schedl, Peter Knees: Preface to the Special Issue on user modeling for personalized interaction with music
19. Amra Delić, Thuy Ngoc Nguyen, Marko Tkalčič: Group decision-making and designing group recommender systems
20. Marko Tkalčič, Bruce Ferwerda: Eudaimonic modeling of moviegoers
21. Bruce Ferwerda, Li Chen, Marko Tkalčič: Editorial
22. Psychological models for personalized human-computer interaction (HCI)
23. Mehdi Elahi, Danial Khosh Kholgh, Mohammad Sina Kiarostami, Sorush Saghari, Shiva Parsa Rad, Marko Tkalčič: Investigating the impact of recommender systems on user-based and item-based popularity bias
24. Ludovico Boratto, Alexander Felfernig, Martin Stettinger, Marko Tkalčič: Preface on the special issue on group recommender systems
25. Gregor Grbec, Nino Bašić, Marko Tkalčič: Ranking footballers with multilevel modeling