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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Bibliographic Details
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
Description
Summary: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.