Text Categorization Using Naive Bayes Algorithm

As the volume of information available on the internet and corporate intranet continues to increase, there is a growing interest in helping people better find, filter, and manage all these resources. Text categorization is one of the techniques that can be applied in this situation. This paper prese...

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Main Author:	Wan Hazimah, Wan Ismail
Format:	Thesis
Language:	eng eng
Published:	2005
Subjects:	QA71-90 Instruments and machines
Online Access:	https://etd.uum.edu.my/1368/1/WAN_HAZIMAH_BT._WAN_ISMAIL.pdf https://etd.uum.edu.my/1368/2/1.WAN_HAZIMAH_BT._WAN_ISMAIL.pdf
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id	my-uum-etd.1368
record_format	uketd_dc
spelling	my-uum-etd.13682013-07-24T12:11:39Z Text Categorization Using Naive Bayes Algorithm 2005-10-26 Wan Hazimah, Wan Ismail Faculty of Information Technology Faculty of Information Technology QA71-90 Instruments and machines As the volume of information available on the internet and corporate intranet continues to increase, there is a growing interest in helping people better find, filter, and manage all these resources. Text categorization is one of the techniques that can be applied in this situation. This paper presents text categorization system based on naive Bayes algorithm. This algorithm has long been used for text categorization tasks. Naive Bayes classifier is based on probability model that integrate strong independence assumptions which often have no bearing in reality. The aims of this project are to categorize the textual document using naive Bayes algorithm and to measure the correctness of the chosen technique for the categorization process. This paper also discusses the experiment in categorizing articles using naive Bayes. The result shows that the accuracy for training is 81.82% whereas the accuracy for testing is 47.62%. 2005-10 Thesis https://etd.uum.edu.my/1368/ https://etd.uum.edu.my/1368/1/WAN_HAZIMAH_BT._WAN_ISMAIL.pdf application/pdf eng validuser https://etd.uum.edu.my/1368/2/1.WAN_HAZIMAH_BT._WAN_ISMAIL.pdf application/pdf eng public masters masters Universiti Utara Malaysia
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
topic	QA71-90 Instruments and machines
spellingShingle	QA71-90 Instruments and machines Wan Hazimah, Wan Ismail Text Categorization Using Naive Bayes Algorithm
description	As the volume of information available on the internet and corporate intranet continues to increase, there is a growing interest in helping people better find, filter, and manage all these resources. Text categorization is one of the techniques that can be applied in this situation. This paper presents text categorization system based on naive Bayes algorithm. This algorithm has long been used for text categorization tasks. Naive Bayes classifier is based on probability model that integrate strong independence assumptions which often have no bearing in reality. The aims of this project are to categorize the textual document using naive Bayes algorithm and to measure the correctness of the chosen technique for the categorization process. This paper also discusses the experiment in categorizing articles using naive Bayes. The result shows that the accuracy for training is 81.82% whereas the accuracy for testing is 47.62%.
format	Thesis
qualification_name	masters
qualification_level	Master's degree
author	Wan Hazimah, Wan Ismail
author_facet	Wan Hazimah, Wan Ismail
author_sort	Wan Hazimah, Wan Ismail
title	Text Categorization Using Naive Bayes Algorithm
title_short	Text Categorization Using Naive Bayes Algorithm
title_full	Text Categorization Using Naive Bayes Algorithm
title_fullStr	Text Categorization Using Naive Bayes Algorithm
title_full_unstemmed	Text Categorization Using Naive Bayes Algorithm
title_sort	text categorization using naive bayes algorithm
granting_institution	Universiti Utara Malaysia
granting_department	Faculty of Information Technology
publishDate	2005
url	https://etd.uum.edu.my/1368/1/WAN_HAZIMAH_BT._WAN_ISMAIL.pdf https://etd.uum.edu.my/1368/2/1.WAN_HAZIMAH_BT._WAN_ISMAIL.pdf
_version_	1747827131386167296

Text Categorization Using Naive Bayes Algorithm

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