Effects of OCR errors on text categorization

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.

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

2001

Author dc:creator

• Mackovski, Lidija K

Contributors dc:contributor

• Kazem Taghva

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

Identifier

https://oasis.library.unlv.edu/rtds/1331

OAI identifier oai:identifier

oai:oasis.library.unlv.edu:rtds-2330