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A framework to cluster temporal data using personalised modelling approach

Othman, Muhaini and Mohamed, Siti Aisyah and Abdullah, Mohd Hafizul Afifi and Mohd Yusof, Munirah and Mohamed, Rozlini (2018) A framework to cluster temporal data using personalised modelling approach. In: Proceedings of the Third International Conference on Soft Computing and Data Mining (SCDM 2018), 06-07 February 2018, Johor, Malaysia.

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Abstract

This research paper is focused on the framework design of temporal data by using personalised modelling approach in order to clus- ter the temporal data. Real world problem on ood occurrences is used as a case study focusing only in Malaysia region. The data are designed according to the criteria needed for temporal data clustering, tested with three clustering techniques including K-means, X-means, and K- medoids. Rapid Miner is used for conducting the clustering processes. Finally, the result from each clustering method is compared to conclude and justify the best clustering approach for clustering temporal data.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Personalised modelling; temporal data; clustering; flood case study
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: Mr. Mohammad Shaifulrip Ithnin
Date Deposited: 29 Aug 2019 03:46
Last Modified: 29 Aug 2019 03:46
URI: http://eprints.uthm.edu.my/id/eprint/11508
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