In this paper, we propose three complementary methods for dealing with most common uncertainty types present in mobile context-aware systems.

This work argues that all of these requirements can be met with a usage of incremental decision tree learning algorithm with modified split criterion, ...

Uncertainty handling is one of the most important aspects of modelling of context-aware systems. It has direct impact on the adaptability, understood as an ...

In this paper we perform comparison of application of different uncertainty modeling approaches to mobile context-aware environments. We also present an ...

Several approaches were developed to solve uncertainty in context knowledge bases, in-cluding probabilistic reasoning, fuzzy logic, or certainty factors.

Bobek, S., Nalepa, G.J.: Uncertainty handling in rule-based mobile context-aware systems. Pervasive and Mobile Computing (2016) https://doi.org/10.1016/j ...

In this chapter, selected practical results of the KnowMe project are discussed and the use of the formal model for uncertainty handling is demonstrated, ...

Context-awareness is a key to enabling intelligent adaptation in pervasive computing applications that need to cope with dynamic and uncertain environments.

This paper presents the use of a possibilistic logic programming framework in a context-aware system to handle user profiles. The framework is able to capture ...

We demonstrate the use of the formal model for uncertainty handling. We distinguish three phases that every context-aware system should pass during the ...