Foundations of a functional approach to knowledge representation.
Artificial Intelligence
Conceptual database design: an Entity-relationship approach
Conceptual database design: an Entity-relationship approach
The logic of knowledge bases
Formal Ontology in Information Systems: Proceedings of the 1st International Conference June 6-8, 1998, Trento, Italy
Data integration: a theoretical perspective
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Foundations of Databases: The Logical Level
Foundations of Databases: The Logical Level
The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
Linguistically motivated large-scale NLP with C&C and boxer
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
DL-Lite: tractable description logics for ontologies
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 4
EQL-lite: effective first-order query processing in description logics
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
AquaLog: an ontology-portable question answering system for the semantic web
ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
The data complexity of the syllogistic fragments of English
Proceedings of the 17th Amsterdam colloquium conference on Logic, language and meaning
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Relational database (DB) management systems provide the standard means for structuring and querying large amounts of data. However, to access such data the exact structure of the DB must be know, and such a structure might be far from the conceptualization of a human being of the stored information. Ontologies help to bridge this gap, by providing a high level conceptual view of the information stored in a DB in a cognitively more natural way. Even in this setting, casual end users might not be familiar with the formal languages required to query ontologies. In this paper we address this issue and study the problem of ontology-based data access by means of natural language questions instead of queries expressed in some formal language. Specifically, we analyze how complex real life questions are and how far from the query languages accepted by ontology-based data access systems, how we can obtain the formal query representing a given natural language question, and how can we handle those questions which are too complex wrt the accepted query language.