Data with semantics: data models and data management
Data with semantics: data models and data management
Federated database systems for managing distributed, heterogeneous, and autonomous databases
ACM Computing Surveys (CSUR) - Special issue on heterogeneous databases
Semantic vs. structural resemblance of classes
ACM SIGMOD Record
A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Semantic similarities between objects in multiple databases
Management of heterogeneous and autonomous database systems
Meaning and grammar (2nd ed.): an introduction to semantics
Meaning and grammar (2nd ed.): an introduction to semantics
A Metadata Approach to Resolving Semantic Conflicts
VLDB '91 Proceedings of the 17th International Conference on Very Large Data Bases
So Far (Schematically) yet So Near (Semantically)
Proceedings of the IFIP WG 2.6 Database Semantics Conference on Interoperable Database Systems (DS-5)
Generating association rules from semi-structured documents using an extended concept hierarchy
CIKM '97 Proceedings of the sixth international conference on Information and knowledge management
The ρ operator: discovering and ranking associations on the semantic web
ACM SIGMOD Record
Semantic and schematic similarities between database objects: a context-based approach
The VLDB Journal — The International Journal on Very Large Data Bases
Information Technology and Management
VirtuE: a formal model of virtual enterprises for information markets
Journal of Intelligent Information Systems
Semantic information brokering: how can a multi-agent approach help?
CIA'99 Proceedings of the 3rd international conference on Cooperative information agents III
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The rapid advances in computer and communication technologies, and their merger, is leading to a global information market place. It will consist of federations of very large number of information systems that will cooperate to varying extents to support the users' information needs. We discuss an approach to information brokering in the above environment. We discuss two of its tasks: information resource discovery, which identifies relevant information sources for a given query, and query processing, which involves the generation of appropriate mapping from relevant but structurally heterogeneous objects. Query processing consists of information focusing and information correlation.Our approach is based on: semantic proximity, which represents semantic similarities based on the context of comparison, and schema correspondences which are used to represent structural mappings and are associated with the context. The context of comparison of the two objects is the primary vehicle to represent the semantics for determining semantic proximity. Specifically, we use a partial context representation to capture the semantics in terms of the assumptions in the intended use of the objects and the intended meaning of the user query. Information focusing is supported by subsequent context comparison. The same mechanism can be used to support information resource discovery. Context comparison leads to changes in schema correspondences that are used to support information correlation.