Computationally Tractable, Conceptually Plausible Classes of Link Matrices for the Inquery Inference Network

Abstract

This paper presents the PIC matrices, a computationally efficient subclass of link matrices that may be considered for the interpretation of query operators in the INQUERY inference network. The PIC class of matrices is formally defined; a defined; 0(n(exp 2)) algorithm, PIC-EVAL, is presented for the evaluation of members of this class; and a proof of the correctness of the algorithm is given. A further specalization of this class that can be evaluated even more efficiently is discussed. Finally, a generalization of the PIC class, for which the input probabilities may be viewed as weighted, is defined, and a simple modification of the PIC-EVAL algorithm that allows for the evaluation of matrices of this extended class is given.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1996
Accession Number
ADA445756

Entities

People

  • Warren R. Greiff

Organizations

  • University of Massachusetts Amherst

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Arithmetic
  • Bayesian Networks
  • Coefficients
  • Computations
  • Computer Science
  • Efficiency
  • Equations
  • Information Operations
  • Information Retrieval
  • Iterations
  • Notation
  • Probability
  • Probability Distributions
  • Test And Evaluation
  • Triangles

Fields of Study

  • Computer science

Readers

  • Computational Linguistics
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Mathematical Modeling and Probability Theory.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms