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Query processing in annotated logic programming: Theory and implementation

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Abstract

Annotated logic is a formalism that has been applied to a variety of situations in knowledge representation, expert database systems, quantitative reasoning, and hybrid databases [6], [13], [19], [20], [21], [22], [23], [24], [30], [33], [35], [36]. Annotated Logic Programming (ALP) is a subset of annotated logics that can be used directly for programming annotated logic applications [22], [23]. A top-down query processing procedure containing elements of constraint solving, called ca-resolution, is developed for ALPs. It simplifies a number of previously proposed procedures, and also improves on their efficiency. The key to its development is in observing that satisfaction, as introduced originally for ALPs, may be naturally generalized. A computer implementation of ca-resolution for ALPs is described which offers important theoretical and practical insights. Strategies for improving its efficiency are discussed.

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Additional information

This material is based upon work supported by the NSF under Grant CCR9225037. A preliminary version of this paper appears in the proceedings of the International Conference on Logic Programming, 1994.

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Leach, S.M., Lu, J.J. Query processing in annotated logic programming: Theory and implementation. J Intell Inf Syst 6, 33–58 (1996). https://doi.org/10.1007/BF00712385

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Keywords

  • expert database systems
  • heterogeneous systems
  • reasoning under uncertainty