Abstract
Query processing plays a fundamental role in current information systems that need to access independent and heterogeneous databases. This paper presents a new approach to querying heterogeneous databases that maps the semantics of query objects onto database schemas. The sematics is captured by the definitions of classes in an ontology, and a similarity function identifies not only equivalent but also semantically similar classes associated with a user’s request. These similar classes are then mapped onto a database schema, which is compared with schemas of heterogeneous databases to obtain entities in the databases that answer the query.
Keywords
- Semantic Similarity
- Semantic Relation
- Relational Schema
- Database Schema
- Query Object
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Rodríguez, M.A., Varas, M. (2002). A Knowledge-Based Approach to Querying Heterogeneous Databases. In: Hacid, MS., Raś, Z.W., Zighed, D.A., Kodratoff, Y. (eds) Foundations of Intelligent Systems. ISMIS 2002. Lecture Notes in Computer Science(), vol 2366. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48050-1_25
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DOI: https://doi.org/10.1007/3-540-48050-1_25
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