- Various aspects of user preference learning and recommender systems2009 | Faculty of Mathematics and Physics
- PrefWork - a framework for the user preference learning methods testing2009 | Faculty of Mathematics and Physics
- Considering data-mining techniques in user preference learning +12008 | Faculty of Mathematics and Physics
- Preference learning by matrix factorization on island models2018 | Faculty of Mathematics and Physics
- Understanding Transparent and Complicated Users as Instances of Preference Learning for Recommender Systems2016 | Faculty of Mathematics and Physics
- Interpreting Web Shop User's Behavioral Patterns as Fictitious Explicit Rating for Preference Learning2014 | Faculty of Mathematics and Physics
- Learning user preferences for top-k querying - improving learning of the higher ranked objects2010 | Faculty of Mathematics and Physics
- Similarity of users' (content-based) preference models for Collaborative filtering in few ratings scenario2012 | Faculty of Mathematics and Physics
- e-Shop User Preferences via User Behavior2014 | Faculty of Mathematics and Physics
- Basis Functions as Pivots in Space of Users Preferences2016 | Faculty of Mathematics and Physics
- Visual E-Commerce Values Filtering Framework with Spatial Database metric2020 | Faculty of Mathematics and Physics
- Graphical E-Commerce Values Filtering Model in Spatial Database Framework2019 | Faculty of Mathematics and Physics
- Monotonization of User Preferences2015 | Faculty of Mathematics and Physics
- Multimodal Implicit Feedback for Recommender Systems2017 | Faculty of Mathematics and Physics
- Evaluating top-k algorithms with various sources of data and user preferences2011 | Faculty of Mathematics and Physics
- Towards Recommender Systems for Police Photo Lineup2017 | Faculty of Mathematics and Physics, Faculty of Arts
- Drug-target interaction prediction: A Bayesian ranking approach2017 | Faculty of Mathematics and Physics