Download Applications of Logic Databases by Oris Friesen, Gilles Gauthier-Villars (auth.), Raghu PDF

By Oris Friesen, Gilles Gauthier-Villars (auth.), Raghu Ramakrishnan (eds.)

The premise in the back of constructing robust declarative database languages is compelling: by means of allowing clients to specify their queries (and their integrity constraints) in a transparent, non-operational method, they make the user's activity more uncomplicated, and supply the database approach with extra possibilities for optimization. Relational database platforms supply a notable evidence that this premise is certainly legitimate. the preferred relational question language, SQL, relies upon relational algebra and calculus, i.e., a small fragment of first-order common sense, and the convenience of writing queries in SQL (in comparability to extra navigational languages) has been a big think about the industrial luck of relational databases. it truly is recognized that SQL has a few very important obstacles, inspite of its good fortune and recognition. significantly, the question language is non-recursive, and help for integrity constraints is proscribed. certainly, spotting those difficulties, the most recent commonplace, SQL-92, presents elevated help for integrity constraints, and it truly is expected that the successor to the SQL-92 common, referred to as SQL3, RECURSIVE UNION operation [1]. common sense database platforms have will contain a targeting those extensions to the relational database paradigm, and a few platforms (e.g., Bull's DEL prototype) have even integrated object-oriented gains (another extension prone to look in SQL3).

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Create basis predicate column (height integer, weight integer, floor ref(floor), x_coord integer, y_coord integer); create basis predicate crane(floor ref(floor), capacity integer); create basis predicate beam(weight integer, thickness integer, floor ref(floor)); Then we define the basis predicates for the architectural data. height integer); create basis predicate wall(height integer, support_beam ref(beam), floor ref(floor)); create basis predicate turbine(x_coord integer, y_coord integer); Now we define a global soft constraint to check that no columns exceed a height greater than twice the floor height.

76-78. , "Urban School Improvement Project Proposal," University of Illinois, May 8, 1992. , "Data Dredging," Data Engineering, Dec. 1990, pp. 58-63. , P. Bayer, A. Lefebvre and V. Kuechenhoff, "EKS, A Short Overview," AAAI-90 Workshop on Knowledge Management Systems. July 1990. edu ABSTRACT This chapter discusses an extended deductive database prototype system, Q-Data, developed by Bellcore to improve data quality through data validation and cleanup. The key technology component of Q-Data is the extended deductive database system LDL++, developed at MCC.

The regulatory application scenario is a good example of knowledge independence: rules governing the proper placement of containers are stated through the mere translation of regulations into logic programming, and do not have to be repeated in each transaction that people use to place the containers. It also demonstrates that rules need only be stated once. Different roles are realized through different means of invocation: to look for dangerous goods too near a given slot, one queries the rule; to check that no two slots contain dangerous goods that are too close together, the rule is used as a soft constraint.

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