Context modelling in fuzzy systems

Fuzzy rule-based systems (FRBS) use the principle of fuzzy sets and fuzzy logic to describe vague and imprecise statements and provide a facility to express the behaviours of the system with a human-understandable language. Fuzzy information, once defined by a fuzzy system, is fixed regardless of the circumstances and therefore makes it very difficult to capture the effect of context on the meaning of the fuzzy terms. While efforts have been made to integrate contextual information into the representation of fuzzy sets, it remains the case that often the context model is very restrictive and/or problem specific. In this work, we introduce a flexible and semantically expressive context representation that can be used in various application scenarios.We also present a practical framework for constructing membership functions of fuzzy sets according to the context within which they are used. An application example concerning the benefits of the new approach in handling context dependency problem over the conventional fuzzy approach are considered.