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Conceptual Information Retrieval

A Case Study in Adaptive Partial Parsing

  • Michael L. Mauldin

Table of contents

  1. Front Matter
    Pages i-xxi
  2. Michael L. Mauldin
    Pages 1-16
  3. Michael L. Mauldin
    Pages 17-38
  4. Michael L. Mauldin
    Pages 39-54
  5. Michael L. Mauldin
    Pages 55-87
  6. Michael L. Mauldin
    Pages 89-107
  7. Michael L. Mauldin
    Pages 109-132
  8. Michael L. Mauldin
    Pages 133-151
  9. Back Matter
    Pages 153-215

About this book

Introduction

The infonnation revolution is upon us. Whereas the industrial revolution heralded the systematic augmentation of human physical limitations by har­ nessing external energy sources, the infonnation revolution strives to augment human memory and mental processing limitations by harnessing external computational resources. Computers can accumulate. transmit and output much more infonnation and in a more timely fashion than more con­ ventional printed or spoken media. Of greater interest, however, is the computer's ability to process, classify and retrieve infonnation selectively in response to the needs of each human user. One cannot drink from the fire hydrant of infonnation without being immediately flooded with irrelevant text. Recent technological advances such as optical character readers only exacerbate the problem by increasing the volume of electronic text. Just as steam and internal combustion engines brought powerful energy sources under control to yield useful work in the industrial revolution, so must we build computational engines that control and apply the vast infonnation sources that they may yield useful knowledge. Information science is the study of systematic means to control, classify, process and retrieve vast amounts of infonnation in electronic fonn. In par­ ticular, several methodologies have been developed to classify texts manually by annies of human indexers, as illustrated quite clearly at the National Library ofMedicine, and many computational techniques have been developed to search textual data bases automatically, such as full-text keyword searches. In general.

Keywords

Parsing control evolution grammar information retrieval knowledge learning memory

Authors and affiliations

  • Michael L. Mauldin
    • 1
  1. 1.Carnegie Mellon UniversityUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4615-4004-5
  • Copyright Information Kluwer Academic Publishers 1991
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4613-6790-1
  • Online ISBN 978-1-4615-4004-5
  • Series Print ISSN 0893-3405
  • Buy this book on publisher's site
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