A machine learning framework for automated text categorization

This dissertation describes a machine learning framework for the development of an automated text categorization system for real-life problems. Conference paper classification will be used as a case study of a life text categorization problem. Unlike documents in benchmark collections, text document...

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Bibliographic Details
Main Author:	Bong, Chih How
Format:	Thesis
Language:	English
Published:	2001
Subjects:	Q Science (General)
Online Access:	http://ir.unimas.my/id/eprint/1697/3/BongCH.pdf
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id	my-unimas-ir.1697
record_format	uketd_dc
spelling	my-unimas-ir.16972023-11-14T01:23:54Z A machine learning framework for automated text categorization 2001 Bong, Chih How Q Science (General) This dissertation describes a machine learning framework for the development of an automated text categorization system for real-life problems. Conference paper classification will be used as a case study of a life text categorization problem. Unlike documents in benchmark collections, text documents such as conference papers tend to be rather heterogeneous having a rich structure with variable length documents where each category consists of a variable number of documents. Faculty of Computer Science and Information Technology 2001 Thesis http://ir.unimas.my/id/eprint/1697/ http://ir.unimas.my/id/eprint/1697/3/BongCH.pdf text en validuser masters Universiti Malaysia Sarawak (UNIMAS) Faculty of Computer Science and Information Technology
institution	Universiti Malaysia Sarawak
collection	UNIMAS Institutional Repository
language	English
topic	Q Science (General)
spellingShingle	Q Science (General) Bong, Chih How A machine learning framework for automated text categorization
description	This dissertation describes a machine learning framework for the development of an automated text categorization system for real-life problems. Conference paper classification will be used as a case study of a life text categorization problem. Unlike documents in benchmark collections, text documents such as conference papers tend to be rather heterogeneous having a rich structure with variable length documents where each category consists of a variable number of documents.
format	Thesis
qualification_level	Master's degree
author	Bong, Chih How
author_facet	Bong, Chih How
author_sort	Bong, Chih How
title	A machine learning framework for automated text categorization
title_short	A machine learning framework for automated text categorization
title_full	A machine learning framework for automated text categorization
title_fullStr	A machine learning framework for automated text categorization
title_full_unstemmed	A machine learning framework for automated text categorization
title_sort	machine learning framework for automated text categorization
granting_institution	Universiti Malaysia Sarawak (UNIMAS)
granting_department	Faculty of Computer Science and Information Technology
publishDate	2001
url	http://ir.unimas.my/id/eprint/1697/3/BongCH.pdf
_version_	1783727898015825920

A machine learning framework for automated text categorization

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