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...
| Main Author: | |
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| Format: | Thesis |
| Language: | English English English |
| Published: |
2011
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| Online Access: | http://eprints.uthm.edu.my/2629/ 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 |
| _version_ | 1848887789893976064 |
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| author | Yanto, Iwan Tri Riyadi |
| author_facet | Yanto, Iwan Tri Riyadi |
| author_sort | Yanto, Iwan Tri Riyadi |
| building | UTHM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T19:59:59Z |
| format | Thesis |
| id | uthm-2629 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| language | English English English |
| last_indexed | 2025-11-15T19:59:59Z |
| publishDate | 2011 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-26292021-11-01T03:31:31Z http://eprints.uthm.edu.my/2629/ Rough clustering for web transactions 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 NonPeerReviewed text en http://eprints.uthm.edu.my/2629/1/24p%20IWAN%20TRI%20RIYADI%20YANTO.pdf text en http://eprints.uthm.edu.my/2629/2/IWAN%20TRI%20RIYADI%20YANTO%20COPYRIGHT%20DECLARATION.pdf text en http://eprints.uthm.edu.my/2629/3/IWAN%20TRI%20RIYADI%20YANTO%20WATERMARK.pdf Yanto, Iwan Tri Riyadi (2011) Rough clustering for web transactions. Masters thesis, Universiti Tun Hussein Malaysia. |
| spellingShingle | QA Mathematics QA76 Computer software Yanto, Iwan Tri Riyadi Rough clustering for web transactions |
| title | 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_short | Rough clustering for web transactions |
| title_sort | rough clustering for web transactions |
| topic | QA Mathematics QA76 Computer software |
| url | http://eprints.uthm.edu.my/2629/ 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 |