CoBase: a scalable and extensible cooperative information system
Journal of Intelligent Information Systems - Special issue on intelligent integration of information
Using explicit ontologies in KBS development
International Journal of Human-Computer Studies
Query approximate answering system for an incomplete DKBS
Fundamenta Informaticae - Special issue: intelligent information systems
Knowledge representation: logical, philosophical and computational foundations
Knowledge representation: logical, philosophical and computational foundations
Formal Ontology in Information Systems: Proceedings of the 1st International Conference June 6-8, 1998, Trento, Italy
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Cooperative Answering through Controlled Query Relaxation
IEEE Expert: Intelligent Systems and Their Applications
Ontology, Metadata, and Semiotics
ICCS '00 Proceedings of the Linguistic on Conceptual Structures: Logical Linguistic, and Computational Issues
Discovery of Surprising Exception Rules Based on Intensity of Implication
PKDD '98 Proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery
Ontologies: A Silver Bullet for Knowledge Management and Electronic Commerce
Ontologies: A Silver Bullet for Knowledge Management and Electronic Commerce
Ontology-based distributed autonomous knowledge systems
Information Systems - Special issue on web data integration
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The paper concerns failing queries in incomplete Distributed Autonomous Information Systems (DAIS) based on attributes which are hierarchical and which semantics at different sites of DAIS may differ. Query q fails in an information system S, if the empty set of objects is returned as an answer. Alternatively, query q can be converted to a new query which is solvable in S. By a refinement of q, we mean a process of replacing q by a new relaxed query, as it was proposed in [2], [7], and [8], which is similar to q and which does not fail in S. If some attributes listed in q have values finer than the values used in S, then rules discovered either locally at S or at other sites of DAIS are used to assign new finer values of these attributes to objects in S. Queries may also fail in S when some of the attributes listed in q are outside the domain of S. To resolve this type of a problem, we extract definitions of such attributes at some of the remote sites for S in DAIS and next use them to approximate q in S. In order to do that successfully, we assume that all involved information systems have to agree on the ontology of some of their common attributes [14], [15], [16]. This paper shows that failing queries can be often handled successfully if knowledge discovery methods are used either to convert them to new queries or to find finer descriptions of objects in S.