Investigations of Human Question Answering

Abstract

This project developed and tested a model of human question answering (called QUEST). QUEST accounts for the answers that adults produce when they answer different categories of open-class questions, such as why, how, when, and what-if. QUEST identifies the information sources for questions and assumes that knowledge is organized in the form of conceptual graph structures containing statement nodes and relational arcs. Example types of structures include goal hierarchies, casual networks, taxonomic hierarchies, and spatial partonomies. Question answering procedures operate systematically on these knowledge structures. An important property of QUEST consists of three convergence mechanisms which narrow down the node space from dozens/hundreds of nodes to a handful of nodes that serve as good answers to a question. (eg)

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1990
Accession Number
ADA218466

Entities

People

  • Arthur C. Graesser

Organizations

  • University of Memphis

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • California
  • Cognitive Science
  • Computational Linguistics
  • Computer Programs
  • Computer Science
  • Computers
  • Databases
  • Education
  • Educational Psychology
  • Information Science
  • Language
  • Linguistics
  • Lisp Programming Language
  • Military Research
  • Natural Languages
  • Psychology

Readers

  • Artificial Intelligence
  • Computer Networking
  • Educational Psychology

Technology Areas

  • Space