Abstract
Semantic query optimisation is the process by which a user query is transformed into a set of alternative queries each of which returns the same answer as the original. The most efficient of these alternatives is then selected, for execution, using standard cost estimation techniques. The query transformation process is based on the use of semantic knowledge in the form of rules which are generated either during the query process itself or are constructed according to defined heuristics. Previous research has tended to focus on constructing rules applicable to single relations and does not take advantage of the additional semantic knowledge, inherent in most databases, associated with relational joins. Our paper seeks to address this weakness by showing how the rule derivation process may be extended to the generation of inter-relational rules using an approach based on inductive learning.
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Lowden, B.G., Robinson, J. (2002). Constructing Inter-relational Rules for Semantic Query Optimisation. In: Hameurlain, A., Cicchetti, R., Traunmüller, R. (eds) Database and Expert Systems Applications. DEXA 2002. Lecture Notes in Computer Science, vol 2453. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46146-9_58
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DOI: https://doi.org/10.1007/3-540-46146-9_58
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