Extending Logic Programs with Description Logic Expressions for the Semantic Web
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| 76407_1.pdf | 128Kb | Adobe PDF | View |
| Title | Extending Logic Programs with Description Logic Expressions for the Semantic Web |
|---|---|
| Author | Shen, Yi-Dong; Wang, Kewen |
| Journal Name | Lecture Notes in Computer Science |
| Editor | Lora Aroyo, Chris Welty, Harith Alani, Jamie Taylor, Abraham Bernstein, Lalana Kagal, Natasha Fridma |
| Year Published | 2011 |
| Place of publication | Germany |
| Publisher | Springer |
| Abstract | Recently much attention has been directed to extending logic programming with description logic (DL) expressions, so that logic programs have access to DL knowledge bases and thus are able to reason with ontologies in the Semantic Web. In this paper, we propose a new extension of logic programs with DL expressions, called normal DL logic programs. In a normal DL logic program arbitrary DL expressions are allowed to appear in rule bodies and atomic DL expressions (i.e., atomic concepts and atomic roles) allowed in rule heads. We extend the key condition of well-supportedness for normal logic programs under the standard answer set semantics to normal DL logic programs and define an answer set semantics for DL logic programs which satisfies the extended well-supportedness condition. We show that the answer set semantics for normal DL logic programs is decidable if the underlying description logic is decidable (e.g. SHOIN or SROIQ). |
| Peer Reviewed | Yes |
| Published | Yes |
| Alternative URI | http://dx.doi.org/10.1007/978-3-642-25073-6_40 |
| Copyright Statement | Copyright 2011 Springer Berlin / Heidelberg. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. The original publication is available at www.springerlink.com |
| Volume | 7031 |
| Page from | 633 |
| Page to | 648 |
| ISSN | 0302-9743 |
| Date Accessioned | 2012-02-20 |
| Date Available | 2012-07-24T22:28:06Z |
| Language | en_US |
| Research Centre | Institute for Integrated and Intelligent Systems |
| Faculty | Faculty of Science, Environment, Engineering and Technology |
| Subject | Artificial Intelligence and Image Processing |
| URI | http://hdl.handle.net/10072/43949 |
| Publication Type | Journal Articles (Refereed Article) |
| Publication Type Code | c1 |
Please use this identifier to cite this record: http://hdl.handle.net/10072/43949
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