AUTOMATIC DOCUMENT CLASSIFICATION. PART II ADDITIONAL EXPERIMENTS,

Abstract

This report presents the results of a series of experiments in the techniques of automatic document classification, and compares two different classification schedules and two methods of automatically classifying documents into categories. It concludes that, while there is no significant difference in the predictive efficiency between the Bayesian and the Factor Score methods, automatic document classification is enhanced by the use of a factor-analytically-derived classification schedule. Approximatel 55 per cent of the documents were automatically and correctly classified. (Author)

Document Details

Document Type
Technical Report
Publication Date
Oct 18, 1963
Accession Number
AD0424911

Entities

People

  • Harold Borko
  • Myrna Bernick

Organizations

  • System Development Corporation

Tags

DTIC Thesaurus Topics

  • Automatic
  • Classification

Readers

  • Aerospace Test and Evaluation
  • Computer Vision.
  • Psychometric Testing or Psychological Assessment.

Technology Areas

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