Rule-Based Statistical Calculations on a Database Abstract.

Abstract

The size of data sets subjected to statistical analysis is increasing as computer technology develops. Quick estimates of statistics rather than exact values are becoming increasingly important to analysts. The authors proposes a new technique for estimating statistics on a database, a top-down alternative to the bottom-up method of sampling. This approach precomputes a set of general-purpose statistics on the database, a database abstract, and then uses a large set of inference rules to make bounded estimates of other, arbitrary statistics requested by users. The inference rules form a new example of an artificial-intelligence expert system. There are several important advantages of this approach over sampling methods, as is demonstrated in part by detailed experimental comparisons for two quite different data bases. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1983
Accession Number
ADA136638

Entities

People

  • N. C. Rowe

Organizations

  • Stanford University

Tags

Communities of Interest

  • Biomedical
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Computational Science
  • Computer Programming
  • Computer Science
  • Computers
  • Data Analysis
  • Data Science
  • Databases
  • Expert Systems
  • Information Processing
  • Information Science
  • Information Systems
  • Language
  • Linear Programming
  • Statistical Analysis
  • Two Dimensional
  • United States

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Artificial Intelligence
  • Geospatial Intelligence and Artificial Intelligence Analytics

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference