A Paraconsistent Tableau Algorithm Based on Sign Transformation in Semantic Web
Abstract
In an open, constantly changing and collaborative environment like the forthcoming Semantic Web, it is reasonable to expect that knowledge sources will contain noise and inaccuracies. It is well known, as the logical foundation of the Semantic Web, description logic is lack of the ability of tolerating inconsistent or incomplete data. Recently, the ability of paraconsistent approaches in Semantic Web is weaker in this paper, we present a tableau algorithm based on sign transformation in Semantic Web which holds the stronger ability of reasoning. We prove that the tableau algorithm is decidable which hold the same function of classical tableau algorithm for consistent knowledge bases.
Cite
@article{arxiv.1301.2146,
title = {A Paraconsistent Tableau Algorithm Based on Sign Transformation in Semantic Web},
author = {Xiaowang Zhang and Guohui Xiao and Zuoquan Lin},
journal= {arXiv preprint arXiv:1301.2146},
year = {2013}
}
Comments
11 pages, in Chinese; the 4th Chinese Semantic Web Symposium (CSWS 2010), Beijing, China