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Rough set based clustering for finding relevant document / Ng Choon Ching

By:

Ng Choon Ching

Material type: Text

TextPublication details: Kuantan, Pahang : UMP, 2013Description: x, 52 p. : ill. (some col.) ; 30 cm. + 1 CD-ROMISBN:

THE0001971(Local)

Subject(s):

Dissertation note: Project paper (Bachelor of Computer Science (Software Engineering) -- Universiti Malaysia Pahang - 2013 Abstract: Searching for relevant documents based on the keywords of particular selected articles are proposed in this thesis. This method is proposed to help user get relevant document based on the articles they selected. The common searching engine will return up to thousand articles where some articles are not really relevant to the searching too. In this paper, rough set-based data mining technique is employed to enhance the result of searching relevant documents. The rough set-based clustering technique, namely MinMin Roughness (MMR) is applied to cluster documents from Wikipedia into groups according to keywords of selected articles in the effort for finding relevant documents. This research is done using dataset of articles from online Wikipedia website. The proposed keywords methods for finding relevant documents will save time during searching progress. This research is expected to be useful for finding relevant documents.

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Holdings ( 2 )
Title notes ( 3 )

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Final Year Report	UMPLIB GAMBANG	CD 7602 \| QA76.9.F5 N43 2013 rs Bc. (Browse shelf(Opens below))	1	Not for loan		0000078847
Final Year Report	UMPLIB PEKAN	QA76.9.F5 N43 2013 rs Bc. (Browse shelf(Opens below))	1	Not for loan		0000078846

Project paper (Bachelor of Computer Science (Software Engineering) -- Universiti Malaysia Pahang - 2013

Bibliography : p. 51-52

Searching for relevant documents based on the keywords of particular selected articles are proposed in this thesis. This method is proposed to help user get relevant document based on the articles they selected. The common searching engine will return up to thousand articles where some articles are not really relevant to the searching too. In this paper, rough set-based data mining technique is employed to enhance the result of searching relevant documents. The rough set-based clustering technique, namely MinMin Roughness (MMR) is applied to cluster documents from Wikipedia into groups according to keywords of selected articles in the effort for finding relevant documents. This research is done using dataset of articles from online Wikipedia website. The proposed keywords methods for finding relevant documents will save time during searching progress. This research is expected to be useful for finding relevant documents.