Searching contexts in paraconsistent rough description logic

Abstract

Query refinement is an interactive process of query modification used to increase or decrease the scope of search results in databases or ontologies. We present a method to obtain optimized query refinements of assertion axioms in the paraconsistent rough description logic $\mathcal {PR_{\textit {ALC}}}$ , a four-valued paraconsistent version of the rough $\mathcal {ALC}$ , which is grounded on Belnap’s Logic. This method is based on the notion of the discernibility matrix commonly used in the process of attribute reduction in the rough set theory. It consists of finding sets of concepts which satisfy the rough set approximation operations in assertion axioms. Consequently, these sets of concepts can be used to restrict or relax queries in this logic. We propose two algorithms to settle this problem of query refinement in $\mathcal {PR_{\textit {ALC}}}$ and show their complexity results. The problem of query restrictions using contextual approximation is proved to have exponential time complexity, while the problem of query relaxations has polynomial space complexity.