Typical description logics are limited to dealing with crisp concepts. It is necessary to add fuzzy features to description logics for management of the fuzzy information. In this paper, we propose extended fuzzy ALCN to enable representation and reasoning for complex fuzzy information. We define syntax structure, semantic interpretation and reasoning problems of the extended fuzzy ALCN, and discuss the reasoning properties inexistent in typical description logics. We also design tableau algorithms of reasoning problems for extended fuzzy ALCN. The tableau algorithms are developed in the style of so-called constraint propagation method. Extended fuzzy ALCN is more expressive than the existing fuzzy description logics and present more wide fuzzy information.
|Number of pages||11|
|Journal||Lecture Notes in Computer Science|
|Issue number||PART I|
|State||Published - 2005|
|Event||Second International Confernce on Fuzzy Systems and Knowledge Discovery, FSKD 2005 - Changsha, China|
Duration: 27 Aug 2005 → 29 Aug 2005