Award Date

1-1-2001

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Computer Science

First Committee Member

Kazem Taghva

Number of Pages

44

Abstract

In this thesis; we report on our experiments on training and categorization of optically recognized documents. In, particular, we present a lexicon-based error correction algorithm to improve the categorization process. This algorithm is based on edit distance techniques and information from highly weighted words in the categorizers.

Keywords

Categorization; Effects; Errors; OCR; Text

Controlled Subject

Computer science

File Format

pdf

File Size

1617.92 KB

Degree Grantor

University of Nevada, Las Vegas

Language

English

Permissions

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Identifier

https://doi.org/10.25669/md4f-jxk0


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