Combining Horn rules and description logics in CARIN
Artificial Intelligence
{\cal A}{\cal L}-log: Integrating Datalog and Description Logics
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Description logic programs: combining logic programs with description logic
WWW '03 Proceedings of the 12th international conference on World Wide Web
On the Analysis of Regulations using Defeasible Rules
HICSS '99 Proceedings of the Thirty-second Annual Hawaii International Conference on System Sciences-Volume 6 - Volume 6
The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
OWL DL vs. OWL flight: conceptual modeling and reasoning for the semantic Web
WWW '05 Proceedings of the 14th international conference on World Wide Web
Position paper: a comparison of two modelling paradigms in the Semantic Web
Proceedings of the 15th international conference on World Wide Web
From human regulations to regulated software agents' behavior
Artificial Intelligence and Law
Decidability of SHIQ with complex role inclusion axioms
Artificial Intelligence
ALCPu: an integration of description logic and general rules
RR'07 Proceedings of the 1st international conference on Web reasoning and rule systems
ESAW'06 Proceedings of the 7th international conference on Engineering societies in the agents world VII
Can OWL and logic programming live together happily ever after?
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
Semantic and computational advantages of the safe integration of ontologies and rules
PPSWR'05 Proceedings of the Third international conference on Principles and Practice of Semantic Web Reasoning
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The representation of information in the Web today is mainly through natural language and its meaning is only interpretable to users who have studied understand the specific natural language. Thus, in the case of the Internal Regulation (IR) of an MSc course of a Greek State University in order to extract an (indispensable) conclusion, one must understand the Greek language, must comprehend the content of the regulation and finally must combine information maybe from many disparate parts of the corpus. For example, if a candidate post-graduate student wanted to know if and how he can attend these courses he should consider all the articles of the IR to find the answer to this question. On the other hand, a computer program could not draw such a conclusion using natural language text. To solve problems of this nature one can use the technologies of the Semantic Web. This paper presents the development of a system that gives solution to these issues, based on Semantic Wed mechanisms, such as ontologies in OWL and rule in SWRL.