Modeling Fuzzy Rules with Description Logics

In real application scenarios, input data and knowledge is often vague. Likewise, it is often the case that exact reasoning over data is impossible due to complex dependencies between input data and target outputs. For practical applications, however, good approximations often suffice, and efficient calculation of an approximate answer is often preferable over complex processing which may take a long time to come up with an exact answer. Fuzzy logic supports both features by providing fuzzy membership functions and fuzzy IF-THEN rule bases. In this paper, we show how fuzzy membership functions and fuzzy rules can be modeled by means of an appropriate description logic and how this can be employed for query answering.