Title
Resolution-based rewriting for Horn- $$mathcal {SHIQ}$$ SHIQ ontologies
Abstract
An important approach to query answering over description logic (DL) ontologies is via rewriting the input ontology and query into languages such as (disjunctive) datalog, for which scalable data saturation systems exist. This approach has been studied for DLs of different expressivities such as DL-Lite, $$\mathcal {ELHI}$$ and Horn-$$\mathcal {SHIQ}$$. When it comes to expressive languages resolution is an important technique that can be applied to obtain the rewritings. This is mainly because it allows for the design of general-purpose algorithms that can be easily lifted to support languages of high expressivity. In the current work we present an efficient resolution-based rewriting algorithm tailor-made for the expressive DL language Horn-$$\mathcal {SHIQ}$$. Our algorithm avoids performing many unnecessary inferences, which is one of the main problems of resolution-based algorithms. This is achieved by careful analysis of the complex axioms structure supported in Horn-$$\mathcal {SHIQ}$$. Moreover, we have implemented the proposed algorithm and obtained very encouraging results when conducting extensive experimental evaluation.
Year
DOI
Venue
2020
10.1007/s10115-019-01345-2
Knowledge and Information Systems
Keywords
DocType
Volume
Query rewriting, Description logics, Ontologies, Resolution
Journal
62
Issue
ISSN
Citations 
1
0219-1377
0
PageRank 
References 
Authors
0.34
20
4
Name
Order
Citations
PageRank
Despoina Trivela1875.62
Giorgos Stoilos2124167.47
Alexandros Chortaras311612.31
Giorgos Stamou4120076.88