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Evidential Nearest-Neighbors Classification for Inductive ABox Reasoning

In the line of our investigation on inductive methods for Semantic Web reasoning, we propose an alternative way for approximate ABox reasoning based on the analogical principle of the nearest-neighbors. Once neighbors of a test individual are selected, a combination rule descending from the Dempster-Shafer theory can join together the evidence provided by the neighbor individuals. We show how to exploit the procedure for determining unknown class- and role-memberships or fillers for datatype properties which may be the basis for many further ABox inductive reasoning algorithms.