Fusing Reasoning Services with Formal Concept Analysis

Description Logic (DL)-based concept modelling formalisms provide a powerful means to ontology reasoning. However, the inevitable "trade-off" between the expressive power and the computational complexity prevents DLs from widely being applied to model problem domains featured by heterogeneous knowledge. This paper envisages a dynamic approach locating, composing and fusing DL-based inferential engines with constraint reasoning systems without modifying underlying inference algorithms form both sides. The fusion process is facilitated by a scheme driven by the Formal Concept Analysis (FCA) that based on a request, composes engines dumped in a virtual Engine Pool. A simple ontology containing both abstract and concrete knowledge is used to demonstrate the working theory of the FCA-driven reasoning engine composition and the applicability of the inference fusion framework.