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Document Type : Latin Dissertation
Language of Document : English
Record Number : 150694
Doc. No : ET22486
Main Entry : Jeffrey Scott Coombs
Title Proper : THESAURUS AIDED LEARNING FOR RULE-BASED CATEGORIZATION OF OCR TEXTS
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : The question posed in this thesis is whether the effectiveness of the rule-basedapproach to automatic text categorization on OCR collections can be improved byusing domain-specific thesauri. A rule-based categorizer was constructed consistingof a C++ program called C-KANT which consults documents and creates a programwhich can be executed by the CLIPS expert system shell. A series of tests usingdomain-specific thesauri revealed that a query expansion approach to rule-based au-tomatic text categorization using domain-dependent thesauri will not improve thecategorization of OCR texts. Although some improvement to categorization could bemade using rules over a mixture of thesauri, the improvements were not significantlylarge.....-...,..tested for theQ1 PC1 bus cardBoth these projects mere sofixare des elopment efforts tonards contributing to dlfferentaspects of Roboucs and lZ1echatronics projects m the Controls and Roboucs Group..
Subject : Electericl tess
: برق
electronic file name : TL45707.pdf
Title and statement of responsibility and : THESAURUS AIDED LEARNING FOR RULE-BASED CATEGORIZATION OF OCR TEXTS [Thesis]
 
 
 
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