Semantic reasoning with uncertain information from unreliable sources

Abstract

Intelligent software agents may significantly benefit from semantic reasoning. However, existing semantic reasoners are based on Description Logics, which cannot handle vague, incomplete, and unreliable knowledge. In this paper, we propose SDL-LiteSDL-Lite which extends DL-LiteRDL-LiteR with subjective opinions to represent uncertainty in knowledge. We directly incorporate trust into the reasoning so that the inconsistencies in the knowledge can be resolved based on trust evidence analysis. Therefore, the proposed logic can handle uncertain information from unreliable sources. We demonstrate how SDL-LiteSDL-Lite can be used for semantic fusion of uncertain information from unreliable sources and show that SDL-LiteSDL-Lite reasoner can estimate the ground truth with a minimal error.