Acquiring Generalizations to Organize Human Databases

Abstract

Five experiments are briefly described in this report, and plans for three further experiments are set forth. We are investigating the consequences of people forming concepts or categories after they've been exposed to a collection of instances (stimulus objects, patterns, events) for which certain features are highly inter-correlated. One primary consequence is that once such regularities are discovered, they are exploited to greatly simplify the recording of new instances into memory. In particular, new instances come to be recorded simply in terms of their belonging to a familiar category plus having a few distinctive features. We've found strong evidence for this kind of coding of instances. A second consequence is that once the category (correlated features) of an instance is identified, the person can focus his learning efforts on recording the distinctive features of the instances, resulting in better memory for this information. In a short-term memory experiment, we've found strong evidence for this strategy. A third consequence of people learning consistently- correlated features of stimuli is that it affects the way they judge the similarity of two instances.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1988
Accession Number
ADA202964

Entities

People

  • Gordon H. Bower
  • John Clapper

Organizations

  • Stanford University

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Air Force
  • Availability
  • Classification
  • Coding
  • Cognitive Science
  • Computer Programming
  • Databases
  • Hierarchies
  • Judgment
  • Notation
  • Psychology
  • Ratings
  • Security
  • Symbols
  • Tape Recorders
  • Training
  • Universities

Fields of Study

  • Biology
  • Psychology

Readers

  • Artificial Intelligence
  • Computer Vision.
  • Educational Psychology