Rough clustering for web transactions
Grouping web transactions into clusters is important in order to obtain better understanding of user's behavior. Currently, the rough approximation-based clustering technique has been used to group web transactions into clusters. It is based on the similarity of upper approximations of tran...
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my-uthm-ep.26292021-11-01T03:31:31Z Rough clustering for web transactions 2011-01 Yanto, Iwan Tri Riyadi QA Mathematics QA76 Computer software Grouping web transactions into clusters is important in order to obtain better understanding of user's behavior. Currently, the rough approximation-based clustering technique has been used to group web transactions into clusters. It is based on the similarity of upper approximations of transactions by given threshold. However, the processing time is still an issue due to the high complexity for finding the similarity of upper approximations of a transaction which used to merge between two or more clusters. In this study, an alternative technique for grouping web transactions using rough set theory is proposed. It is based on the two similarity classes which is nonvoid intersection. The technique is implemented in MATLAB ® version 7.6.0.324 (R2008a). The two UCI benchmark datasets taken from: http:/kdd.ics.uci.edu/ databases/msnbc/msnbc.html and http:/kdd.ics.uci.edu/databases/ Microsoft / microsoft.html are opted in the simulation processes. The simulation reveals that the proposed technique significantly requires lower response time up to 62.69 % and 66.82 % as compared to the rough approximation-based clustering, severally. Meanwhile, for cluster purity it performs better until 2.5 % and 14.47%, respectively. 2011-01 Thesis http://eprints.uthm.edu.my/2629/ http://eprints.uthm.edu.my/2629/1/24p%20IWAN%20TRI%20RIYADI%20YANTO.pdf text en public http://eprints.uthm.edu.my/2629/2/IWAN%20TRI%20RIYADI%20YANTO%20COPYRIGHT%20DECLARATION.pdf text en staffonly http://eprints.uthm.edu.my/2629/3/IWAN%20TRI%20RIYADI%20YANTO%20WATERMARK.pdf text en validuser mphil masters Universiti Tun Hussein Malaysia Fakulti Sains Komputer dan Teknologi Maklumat |
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Universiti Tun Hussein Onn Malaysia |
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UTHM Institutional Repository |
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QA Mathematics QA76 Computer software |
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QA Mathematics QA76 Computer software Yanto, Iwan Tri Riyadi Rough clustering for web transactions |
description |
Grouping web transactions into clusters is important in order to obtain better
understanding of user's behavior. Currently, the rough approximation-based
clustering technique has been used to group web transactions into clusters. It is based
on the similarity of upper approximations of transactions by given threshold.
However, the processing time is still an issue due to the high complexity for finding
the similarity of upper approximations of a transaction which used to merge between
two or more clusters. In this study, an alternative technique for grouping web
transactions using rough set theory is proposed. It is based on the two similarity
classes which is nonvoid intersection. The technique is implemented in MATLAB
®
version 7.6.0.324 (R2008a). The two UCI benchmark datasets taken from:
http:/kdd.ics.uci.edu/ databases/msnbc/msnbc.html and
http:/kdd.ics.uci.edu/databases/ Microsoft / microsoft.html are opted in the
simulation processes. The simulation reveals that the proposed technique
significantly requires lower response time up to 62.69 % and 66.82 % as compared to
the rough approximation-based clustering, severally. Meanwhile, for cluster purity it
performs better until 2.5 % and 14.47%, respectively. |
format |
Thesis |
qualification_name |
Master of Philosophy (M.Phil.) |
qualification_level |
Master's degree |
author |
Yanto, Iwan Tri Riyadi |
author_facet |
Yanto, Iwan Tri Riyadi |
author_sort |
Yanto, Iwan Tri Riyadi |
title |
Rough clustering for web transactions |
title_short |
Rough clustering for web transactions |
title_full |
Rough clustering for web transactions |
title_fullStr |
Rough clustering for web transactions |
title_full_unstemmed |
Rough clustering for web transactions |
title_sort |
rough clustering for web transactions |
granting_institution |
Universiti Tun Hussein Malaysia |
granting_department |
Fakulti Sains Komputer dan Teknologi Maklumat |
publishDate |
2011 |
url |
http://eprints.uthm.edu.my/2629/1/24p%20IWAN%20TRI%20RIYADI%20YANTO.pdf http://eprints.uthm.edu.my/2629/2/IWAN%20TRI%20RIYADI%20YANTO%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/2629/3/IWAN%20TRI%20RIYADI%20YANTO%20WATERMARK.pdf |
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