Spontaneous Analogy by Piggybacking on a Perceptual System

Abstract

Most computational models of analogy assume they are given a delineated source domain and often a specified target domain. These systems do not address how analogs can be isolated from large domains and spontaneously retrieved from long-term memory, a process we call spontaneous analogy. We present a system that represents relational structures as feature bags. Using this representation, our system leverages perceptual algorithms to automatically create an ontology of relational structures and to efficiently retrieve analogs for new relational structures from long-term memory. We provide a demonstration of our approach that takes a set of unsegmented stories, constructs an ontology of analogical schemas (corresponding to plot devices), and uses this ontology to efficiently find analogs within new stories, yielding significant time-savings over linear analog retrieval at a small accuracy cost.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2013
Accession Number
ADA602743

Entities

People

  • David W. Aha
  • Marc Pickett

Organizations

  • United States Naval Research Laboratory

Tags

DTIC Thesaurus Topics

  • Accuracy
  • Algorithms
  • Artificial Intelligence
  • Coding
  • Cognitive Science
  • Computer Programming
  • Computer Programs
  • Demonstrations
  • Digital Information
  • Information Operations
  • Military Research
  • Models
  • Ontologies
  • Perception
  • Visual Cortex

Fields of Study

  • Computer science

Readers

  • Artificial Intelligence
  • Computer Vision.
  • Database Systems and Applications