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 $\mathcal {S}\textsf {DL}\text {-}\textsf {Lite}$ which extends $\textsf {DL}\text {-}\textsf {Lite}_{{R}}$ 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 $\mathcal {S}\textsf {DL}\text {-}\textsf {Lite}$ can be used for semantic fusion of uncertain information from unreliable sources and show that $\mathcal {S}\textsf {DL}\text {-}\textsf {Lite}$ reasoner can estimate the ground truth with a minimal error.

Research was sponsored by the U.S. Army Research Laboratory and the U.K. Ministry of Defence and was accomplished under Agreement Numbers W911NF-06-3-0001 and W911NF-14-1-0199. The views and conclusions contained in this document are those of the author(s) and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Army Research Laboratory, the U.S. Government, the U.K. Ministry of Defence or the U.K. Government. The U.S. and U.K. Governments are authorized to reproduce and distribute reprints for Goverment purposes notwithstanding any copyright notation hereon. Dr. Şensoy thanks to the U.S. Army Research Laboratory for its support under grant W911NF-14-1-0199 and The Scientific and Technological Research Council of Turkey (TUBITAK) for its support under grant 113E238.