Award Date

1-1-1996

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

Number of Pages

51

Abstract

In this thesis we describe a spelling correction system designed specifically for OCR (Optical Character Recognition) generated text that selects candidate words through the use of information gathered from multiple knowledge sources. This system for text correction is based on static and dynamic device mappings, approximate string matching, and n-gram analysis. Our statistically based, Bayesian system incorporates a learning feature that collects confusion information at the collection and document levels. An evaluation of the new system is presented as well.

Keywords

Correction; Errors; Interactive; OCR; Spelling; System; Text

Controlled Subject

Computer science

File Format

pdf

File Size

1269.76 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

Permissions

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Identifier

https://doi.org/10.25669/t1t6-9psi


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