Title
Completion Rules for Uncertainty Reasoning with the Description Logic ALC
Abstract
Description Logics (DLs) are gaining more popularity as the foundation of ontology languages for the Semantic Web. On the other hand, uncertainty is a form of deficiency or imperfection commonly found in the realworld information/data. In recent years, there has been an increasing interest in extending the expressive power of DLs to support uncertainty, for which a number of frameworks have been proposed. In this paper, we introduce an extension of DL (ACC) that unifies and/or generalizes a number of existing approaches for DLs with uncertainty. We first provide a classification of the components of existing frameworks for DLs with uncertainty in a generic way. Using this as a basis, we then discuss ways to extend these components with uncertainty, which includes the description language, the knowledge base, and the reasoning services. Detailed explanations and examples are included to describe the proposed completion rules.
Year
DOI
Venue
2006
10.1007/978-0-387-34347-1_14
Semantic Web and Beyond-Computing for Human Experience
Keywords
Field
DocType
expressive power,semantic web,knowledge base,description logic
Knowledge representation and reasoning,Autoepistemic logic,Programming language,Computer science,Multimodal logic,Description logic,Semantic Web,Deductive reasoning,Higher-order logic,Ontology language
Conference
Volume
ISSN
Citations 
2
1559-7474
4
PageRank 
References 
Authors
0.47
13
3
Name
Order
Citations
PageRank
Volker Haarslev11831250.65
Hsueh-Ieng Pai2463.26
Nematollaah Shiri328028.31