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- W2783504828 abstract "This research paper is focused on the framework design of temporal data by using personalised modelling approach in order to cluster the temporal data. Real world problem on flood 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." @default.
- W2783504828 created "2018-01-26" @default.
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- W2783504828 date "2018-01-01" @default.
- W2783504828 modified "2023-10-12" @default.
- W2783504828 title "A Framework to Cluster Temporal Data Using Personalised Modelling Approach" @default.
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- W2783504828 doi "https://doi.org/10.1007/978-3-319-72550-5_18" @default.
- W2783504828 hasPublicationYear "2018" @default.
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