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University of Nevada, Las Vegas

Feature recognition in OCR text

Abstract

dc:description.abstract

This thesis investigates the recognition and extraction of special word sequences, representing concepts, from OCR text. Unlike general index terms, concepts can consist of one or more terms that combined, have higher retrieval value than the terms alone (i.e. acronyms, proper nouns, phrases). An algorithm to recognize acronyms and their definitions will be presented. An evaluation of the algorithm will also be presented.

Degree

thesis:*
Name thesis:degree_name
Master of Science (MS)
Level thesis:degree_level
Thesis
Discipline thesis:degree_discipline
Computer Science
Grantor dc:publisher
University of Nevada, Las Vegas
Year
1996

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Gilbreth, Jeffrey Todd
Contributors dc:contributor
  • Kazem Taghva

Rights

dc:rights
Statement dc:rights
  • IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/
Language dc:language
English

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:oasis.library.unlv.edu:rtds-1586

Chain of custody

source
Harvested from
University of Nevada - Las Vegas
Base URL
oasis.library.unlv.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

Gilbreth, Jeffrey Todd. Feature recognition in OCR text. Thesis thesis, University of Nevada, Las Vegas, 1996. https://doi.org/10.25669/ar50-yge7