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Comparing naive bayes and support vector machines on Sarawak gazette named entity recognition

This paper presents the report of Final Year Project 2 Comparing Naive Bayes and Support Vector Machines on Sarawak Gazette Named Entity Recognition. The need to annotate automatically the Sarawak Gazette is essential to allow the SAGA searchable through Named Entities (NEs). Hence, this paper obje...

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Main Author: Wan Muhammad Faisal, Wan Tamlikha
Format: Final Year Project Report
Language:English
English
Published: Universiti Malaysia Sarawak, (UNIMAS) 2015
Subjects:
T Technology (General)
Online Access:http://ir.unimas.my/id/eprint/38981/1/WAN%20MUHAMMAD%20FAISAL%20%2824%20pgs%29.pdf
http://ir.unimas.my/id/eprint/38981/4/Wan%20M%20Faisal%20ft.pdf
http://ir.unimas.my/id/eprint/38981/
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spelling my.unimas.ir.389812024-09-02T06:56:56Z http://ir.unimas.my/id/eprint/38981/ Comparing naive bayes and support vector machines on Sarawak gazette named entity recognition Wan Muhammad Faisal, Wan Tamlikha T Technology (General) This paper presents the report of Final Year Project 2 Comparing Naive Bayes and Support Vector Machines on Sarawak Gazette Named Entity Recognition. The need to annotate automatically the Sarawak Gazette is essential to allow the SAGA searchable through Named Entities (NEs). Hence, this paper objective is to apply Naive Bayes on the Sarawak Gazette for Named entity recognition along with Support Vector Machine to compare the accuracy of Naive Bayes and Support Vector Machine techniques on Sarawak Gazette named entity recognition.. Moreover, this paper also reviews and analyzes related papers from other researchers regarding the implementation of Supervised Machine Learning to find the best technique to annotate SAGA. A methodology is introduced to explain the flow of the project and the element it carry. This project is implemented in WEKA environment software. The comparison is done after conducting various test method to find the most accurate. The result is compare and analyze. Universiti Malaysia Sarawak, (UNIMAS) 2015 Final Year Project Report NonPeerReviewed text en http://ir.unimas.my/id/eprint/38981/1/WAN%20MUHAMMAD%20FAISAL%20%2824%20pgs%29.pdf text en http://ir.unimas.my/id/eprint/38981/4/Wan%20M%20Faisal%20ft.pdf Wan Muhammad Faisal, Wan Tamlikha (2015) Comparing naive bayes and support vector machines on Sarawak gazette named entity recognition. [Final Year Project Report] (Unpublished)
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
English
topic T Technology (General)
spellingShingle T Technology (General)
Wan Muhammad Faisal, Wan Tamlikha
Comparing naive bayes and support vector machines on Sarawak gazette named entity recognition
description This paper presents the report of Final Year Project 2 Comparing Naive Bayes and Support Vector Machines on Sarawak Gazette Named Entity Recognition. The need to annotate automatically the Sarawak Gazette is essential to allow the SAGA searchable through Named Entities (NEs). Hence, this paper objective is to apply Naive Bayes on the Sarawak Gazette for Named entity recognition along with Support Vector Machine to compare the accuracy of Naive Bayes and Support Vector Machine techniques on Sarawak Gazette named entity recognition.. Moreover, this paper also reviews and analyzes related papers from other researchers regarding the implementation of Supervised Machine Learning to find the best technique to annotate SAGA. A methodology is introduced to explain the flow of the project and the element it carry. This project is implemented in WEKA environment software. The comparison is done after conducting various test method to find the most accurate. The result is compare and analyze.
format Final Year Project Report
author Wan Muhammad Faisal, Wan Tamlikha
author_facet Wan Muhammad Faisal, Wan Tamlikha
author_sort Wan Muhammad Faisal, Wan Tamlikha
title Comparing naive bayes and support vector machines on Sarawak gazette named entity recognition
title_short Comparing naive bayes and support vector machines on Sarawak gazette named entity recognition
title_full Comparing naive bayes and support vector machines on Sarawak gazette named entity recognition
title_fullStr Comparing naive bayes and support vector machines on Sarawak gazette named entity recognition
title_full_unstemmed Comparing naive bayes and support vector machines on Sarawak gazette named entity recognition
title_sort comparing naive bayes and support vector machines on sarawak gazette named entity recognition
publisher Universiti Malaysia Sarawak, (UNIMAS)
publishDate 2015
url http://ir.unimas.my/id/eprint/38981/1/WAN%20MUHAMMAD%20FAISAL%20%2824%20pgs%29.pdf
http://ir.unimas.my/id/eprint/38981/4/Wan%20M%20Faisal%20ft.pdf
http://ir.unimas.my/id/eprint/38981/
_version_ 1809154935791550464
score 13.211869

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