Document categorization using Machine learning techniques

In order to gain information from huge amount of text more efficiently and accurately, readers may use a system which can automatically categorize input text files and generate summary for each categories. The more precise outcomes from the system, the more less time spending on searching of reading...

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Main Author: Hu, Jing
Other Authors: Mao, Kezhi
Format: Final Year Project
Language:English
Published: 2014
Subjects:
Online Access:http://hdl.handle.net/10356/61495
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-614952023-07-07T17:13:02Z Document categorization using Machine learning techniques Hu, Jing Mao, Kezhi School of Electrical and Electronic Engineering DRNTU::Engineering::Computer science and engineering::Information systems::Information systems applications In order to gain information from huge amount of text more efficiently and accurately, readers may use a system which can automatically categorize input text files and generate summary for each categories. The more precise outcomes from the system, the more less time spending on searching of reading . In this project, implementing Machine Learning technique – Naïve Bayes learning algorithm--on text classification and generating an extractive summary for each categories are two main functions. Relative research works on Machine Learning and Text Mining are exhibited in details. The experiment results are presented and discussed. Aim to achieving better performance on text mining, future works are also introduced. Bachelor of Engineering 2014-06-10T09:23:41Z 2014-06-10T09:23:41Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/61495 en Nanyang Technological University 74 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Information systems::Information systems applications
spellingShingle DRNTU::Engineering::Computer science and engineering::Information systems::Information systems applications
Hu, Jing
Document categorization using Machine learning techniques
description In order to gain information from huge amount of text more efficiently and accurately, readers may use a system which can automatically categorize input text files and generate summary for each categories. The more precise outcomes from the system, the more less time spending on searching of reading . In this project, implementing Machine Learning technique – Naïve Bayes learning algorithm--on text classification and generating an extractive summary for each categories are two main functions. Relative research works on Machine Learning and Text Mining are exhibited in details. The experiment results are presented and discussed. Aim to achieving better performance on text mining, future works are also introduced.
author2 Mao, Kezhi
author_facet Mao, Kezhi
Hu, Jing
format Final Year Project
author Hu, Jing
author_sort Hu, Jing
title Document categorization using Machine learning techniques
title_short Document categorization using Machine learning techniques
title_full Document categorization using Machine learning techniques
title_fullStr Document categorization using Machine learning techniques
title_full_unstemmed Document categorization using Machine learning techniques
title_sort document categorization using machine learning techniques
publishDate 2014
url http://hdl.handle.net/10356/61495
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