Recommender systems aim to propose potentially interesting items to a user based on his preferences or previous interaction with the system. In the last decade, researcher found out that known recommendation techniques are not sufficient to predict user decisions. It has been noticed that user preferences strongly depend on the context in which he currently is. This raises new challenges for the researchers such as how to obtain...

Przedstawiono rozwój medycznego systemu komputerowego do badań endoskopowych Endoscopy Recommender System ze szczególnym zwróceniem uwagi na rozwój architektury systemu i bazy danych. Opisano wpływ ewolucji technologii i wymagań systemowych na podejście do magazynowania i zarządzania danymi pacjentów. Omówiono architekturę nowego systemu oraz metodologię wprowadzania zmian w systemie.

Context-aware Recommender Systems aim to provide users with the most adequate recommendations for their current situation. However, an exact context obtained from a user could be too specific and may not have enough data for accurate rating prediction. This is known as the data sparsity problem. Moreover, often user preference representation depends on the domain or the specific recommendation approach used. Therefore, a big effort...

Recommender systems are software tools and techniques which aim at suggesting new items that may be of interest to a user. This dissertation is focused on four problems in recommender systems domain. The first one is context-awareness, i.e. how to obtain relevant contextual information, how to model user preferences in a context and use them to make predictions. The second one is multi-domain recommendation, which aim at suggesting...