An Expert System for Searching in Full-Text

Abstract

This project applies expert system technology to the task of searching online full-text documents. We are developing an intelligent search intermediary to help end-users locate relevant passages in large full-text databases. Our expert system automatically reformulates contextual Boolean queries to improve search results and presents retrieved passages in decreasing order of estimated relevance. It differs from other intelligent database functions in two ways: it works with semantically unprocessed text and the expert systems contains a knowledge base of search strategies independent of any particular contend domain. The goals for our current project are to demonstrate the feasibility of the approach and to evaluate the effectiveness of the system through a controlled experiment. While the work we report here has limited objectives, the system and techniques are general and can be extended to large, real-world databases. Information science.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1988
Accession Number
ADA201091

Entities

People

  • John B. Smith
  • Susan Gauch

Organizations

  • University of North Carolina at Chapel Hill

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Computer Architecture
  • Computer Programs
  • Computers
  • Computing System Architectures
  • Database Management Systems
  • Databases
  • Expert Systems
  • Frequency
  • Indexes
  • Information Processing
  • Information Retrieval
  • Language
  • Natural Language Processing
  • Natural Languages
  • User Interface
  • User Interface Engineering

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Geospatial Intelligence and Artificial Intelligence Analytics
  • Systems Analysis and Design