RoCeT: Rough Clustering for web Transactions(<Special Issue>SOFT COMPUTING METHODOLOGIES AND ITS APPLICATIONS)

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概要

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• 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. 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. On, the other hand, the problem of more than one transaction under given threshold is not addressed. In this paper, we propose RoCeT model for grouping web transactions using rough set theory. It is based on the two similarity classes which are nonvoid intersection.

• バイオメディカル・ファジィ・システム学会の論文

著者

• Mustafa Mat

  Faculty of Information Technology and Multimedia Universiti Tun Hussein Onn Malaysia

• Iwan Tri

  Department of Mathematics Universiti Tun Hussein Onn Malaysia

• Tutut Herawan

  Department of Mathematics Education Universitas Ahmad Dahlan,Universiti Tun Hussein Onn Malaysia

• Tutut Herawan

  Department of Mathematics Education Universitas Ahmad Dahlan,Universiti Tun Hussein Onn Malaysia:Faculty of Information Technology and Multimedia Universiti Tun Hussein Onn Malaysia

関連論文

• RoCeT: Rough Clustering for web Transactions(SOFT COMPUTING METHODOLOGIES AND ITS APPLICATIONS)

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