A DL-based Approach for Product Knowledge Reasoning

In order to capture knowledge of complicated product model, the expressive language ALCNHR^+ K(D) is introduced. It cannot only be able to represent knowledge about concrete domain and constraints, but also rules in some sense of closed world semantic model hypothesis. Also the paper takes an extension to the traditional description logic (DL) reasoning method by means of decomposing complicated hybrid concepts into partitions. An approach that automatically decomposes the whole knowledge base into description logic compatible one and constraints solver one is proposed. Our arguments are two-fold. First, complex DLs with expressive ability lack effective reasoning ability. Second, we are concerned with how to reason effectively with the combination of inferences from distributed heterogeneous reasoner.