Michal Kompan

Research areas: personalised recommendations, machine learning, artificial intelligence, information retrieval

Position: Expert Researcher

Michal focuses on recommender systems, machine learning, user modeling, and information retrieval. His research is focused on predictive modeling and customer behavior (e.g., churn prediction, next-item recommendation), as well as content-based adaptive models. He specifically addresses recommender system diversity, fairness and transparency.

As a teacher, he has supervised more than 50 Bachelor’s and Master’s theses. To support the community, he has served as a reviewer or/and program committee member at several international conferences, such as RecSys, ADBIS, Hypertext, UMAP and SMAP. He is a reviewer for several international journals in Springer, IEEE, ACM, Taylor&Francis and Inderscience.

He is also a member of Slovak.AI, ACM, IEEE and the Slovak informatics society. He has participated in many research projects in co-operation with firms such as Exponea, ZlavaDna, SME, Piano media and Orange SK.

Selected achievements

Member of the excellence team PeWe of Slovak University of Technology in Bratislava, lead prof. Mária Bieliková

Professional Service

  • Program or organizing committee member:
    • ACM Recommender Systems
    • User Modelling, Adaptation and Personalization
    • Workshop on Semantic and Social Media Adaptation & Personalization
    • Advances in Databases and Information Systems
  • Reviewer for:
    • Neural Computing and Applications 
    • Journal of Information Processing and Management
    • IEEE Transactions on Systems, Man and Cybernetics: Systems
    • International Journal of Continuing Engineering Education and Life-Long Learning
    • International Journal of Artificial Intelligence in Education
    • Journal of Organizational Computing and Electronic Commerce
    • IEEE Transactions on Learning Technologies
  • Member of:
    • Institute of Electrical and Electronics Engineers
    • Association for Computing Machinery (senior member)
    • Slovak Society for Computer Science

Selected Projects

Modeling, Prediction and Evaluation of User Behavior Based on the Web Interaction for Adaptation and Personalization

VEGA 1/0667/18. 2018-2020, Kompan, M. – principal investigator

Analysis and Proposal of Methods and Models for Multilingual Content Generated by Users in Online Big Data Space Based on Machine Learning

VEGA 1/0725/19. 2019-2020, Bielikova, M. – principal investigator

Automated Recognition of Antisocial Behaviour in Online Communities

APVV-17-0267. 2018-2020, Partners: Comenius University in Bratislava, Technical University in Kosice, Navrat, P. – principal investigator

Human Information Behavior in the Digital Space

APVV-15-0508. 2016-2020, Partner: Comenius University in Bratislava, Bielikova, M. – principal investigator

Adaptation of Access to Information and Knowledge Artifacts Based on Interaction and Collaboration Within Web

VEGA 1/0646/15. 2015-2018, Bielikova, M. – principal investigator

Selected Student Supervising

PhD

  • Vitek Andrej – Modeling of Player’s Behaviour in Free-To-Play Games. Ongoing.

Master

  • Ondrej Unger – User behavior pattern recognition. Ongoing.
  • Markovičová Viktória – User style modeling with temporal dynamics. Ongoing.
  • Pekarčík Daniel – Personalized recommendation considering sequence of interactions. Ongoing.
  • Džurman Kamil – Preference-based user model for e-commerce. Ongoing.
  • Balážová Michaela – Identification of Fake News on the Web. Defended 2019.
  • Blanárik Patrik – Meta-recommender: Adaptive selection of recommender approach. Defended 2019.
  • Kalafut Matúš – Graph-based recommender. Defended 2019.
  • Valčičák Miroslav – Product popularity prediction in e-commerce. Defended 2019.
  • Tibenský Peter – Products recommendation. Defended 2018.
  • Roštár Marek – Image enhanced personalised recommendation. Defended 2017.
  • Berger Patrik – Customer churn prediction in e-commerce. Defended 2017.
  • Hunka Mário – Scalable personalised recommendation. Defended 2017.
  • Lieskovský Adam – Scalable personalised recommendation. Defended 2015.
  • Svrček Martin – Visualization of generated recommendations. Defended 2015.
  • Kaššák Ondrej – Group recommendation for TV. Defended 2013.
  • Lačný Jozef – Personalised recommendation in e-learning. Defended 2012.

Bachelor

  • Unger Ondrej – Personalised recommendation on the Web. Defended 2019.
  • Tomaštík Nikolas – Personalised recommendation on the Web. Defended 2019.
  • Lam Tuan Dung – Customer behavior prediction in e-commerce. Defended 2018.
  • Balážová Michaela – Customer behavior prediction in e-commerce. Defended 2018.
  • Pitoňák Ondrej – Advanced search and visualization. Defended 2017.
  • Bachárová Zuzana – Customer behavior prediction. Defended 2017.
  • Kaššák Ondrej – Named entity recognition for Slovak. Defended 2012.