Representing Uncertain Concepts in Rough Description Logics via Contextual Indiscernibility Relations.
URSW (LNCS Vol.)(2013)
摘要
We investigate on modeling uncertain concepts via rough description logics, which are an extension of traditional description logics by a simple mechanism to handle approximate concept definitions through lower and upper approximations of concepts based on a rough-set semantics. This allows to apply rough description logics for modeling uncertain knowledge. Since these approximations are ultimately grounded on an indiscernibility relationship, the paper explores possible logical and numerical ways for defining such relationships based on the considered knowledge. In particular, the notion of context is introduced, allowing for the definition of specific equivalence relationships, to be used for approximations as well as for determining similarity measures, which may be exploited for introducing a notion of tolerance in the indiscernibility.
更多查看译文
关键词
description logic
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络