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Deductive Planning and Pathfinding for Relational Data Bases

  • Charles Kellogg
  • Philip Klahr
  • Larry Travis

Abstract

Inference planning techniques have been implemented and incorporated within a prototype deductive processor designed to support the extraction of information implied by, but not explicitly included in, the contents of a relationally structured data base, Deductive pathfinding and inference planning are used to select small sets of relevant premises and to construct skeletal derivations. When these “skeletons” are verified, the system uses them as plans to create data-base access strategies that guide the retrieval of data values, to assemble answers to user requests, and to produce proofs supporting those answers. Several examples are presented to illustrate the current capability of the prototype Deductively Augmented Data Management (DADM) system.

Keywords

Semantic Network Conjunctive Normal Form Inference Plan Search Request Control Processor 
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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Copyright information

© Plenum Press, New York 1978

Authors and Affiliations

  • Charles Kellogg
    • 1
  • Philip Klahr
    • 1
  • Larry Travis
    • 2
  1. 1.System Development CorporationSanta MonicaUSA
  2. 2.University of WisconsinMadisonUSA

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