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:
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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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