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- W1764037604 abstract "We assume that there is a deductive database 〈D, C〉, where D is a set of stratified rules and facts and C a set of constraints. Querying a database means returning all ground instances of the query which are true in the well defined standard model M D induced by D. Given a query Q it is transformed into a new query Q′, such that Q′ will be less costly to be evaluated than Q, and such that Q′ is guaranteed to return the same answer provided that the constraints and rules are satisfied by MD. This transformation is called Semantic Query Optimization (SQO). First we show four ways of transforming a query into a new one. This assures high flexibility for runtime SQO. Afterwards, the method is adapted in order to simplify (may be at compile time) the rules and constraints. The proposed simplifications are such that M D remains the same and such that the simplfied database is consistent iff the original one was. Henceforth, the inference process is heavily improved due to the simplified rules, and the work to be done to check the integrity is reduced since the constraints are simplified. Finally, we turn to query evaluation again and show when a rule may be ignored during the evaluation of a query." @default.
- W1764037604 created "2016-06-24" @default.
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- W1764037604 date "1991-01-01" @default.
- W1764037604 modified "2023-09-27" @default.
- W1764037604 title "Semantic improvement of deductive databases" @default.
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- W1764037604 doi "https://doi.org/10.1007/3-540-54009-1_16" @default.
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