01929nam a2200265 a 4500 vtls000077203 KUKTEM 20251114204604.0 140403t2013 my a f m 000 0 eng d THE0001971(Local) 201905131548 yusri 201404031355 Fida UMP QA76.9.F5 N43 2013 rs Bc. Ng Choon Ching Rough set based clustering for finding relevant document / Ng Choon Ching Kuantan, Pahang : UMP, 2013 x, 52 p. : ill. (some col.) ; 30 cm. + 1 CD-ROM 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. File organization (Computer science) Document clustering Application software Development 0 0 0 1 20000 20000 2019-09-04 0 QA76.9.F5 N43 2013 rs Bc. 0000078846 2019-09-04 00:00:00 1 2019-09-04 PSM 0 0 0 1 10000 10000 2019-09-04 0 CD 7602 | QA76.9.F5 N43 2013 rs Bc. 0000078847 2019-09-04 00:00:00 1 2019-09-04 PSM VIRTUA40 4630 4636 VTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5020*5040*5200*6500*6501*6502*9992