A Test-Case Based Approach to Bayesian Knowledge Base Incompleteness Detection and Correction

Abstract

This work develops tools and techniques to identify particular Bayesian Knowledge Base (BKB) incompletenesses, and to modify the existing knowledge-base (KB) structure to correct these problems. The methodology performs manually or automatically, informing the user of either problems causing the incompleteness, or of details resulting from the automatic knowledge-base correction. The proposed methodology is designed for integration with BVAL, to augment BVAL's validation techniques.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1996
Accession Number
ADA320697

Entities

People

  • Louise J. Lyle

Organizations

  • Air Force Institute of Technology

Tags

DTIC Thesaurus Topics

  • Acquisition
  • Air Force
  • Artificial Intelligence
  • Bayesian Networks
  • Computers
  • Control Systems
  • Data Mining
  • Detection
  • Engineering
  • Engineers
  • Expert Systems
  • Graphical User Interface
  • Inference Engines
  • Probability
  • Random Variables
  • Robotics
  • Water Quality

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Information Retrieval