Search Results - (( framework application mining algorithm ) OR ( java implementation phase algorithm ))

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    An Efficient Data Structure for General Tree-Like Framework in Mining Sequential Patterns Using MEMISP by Saputra, Dhany, Rambli, Dayang R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of applications. …”
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    Conference or Workshop Item
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    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…All the algorithm for the engine has been developed by using Java script language. …”
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    Thesis
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    Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

    Published 2007
    “…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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    Conference or Workshop Item
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    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar by Tengku Jaafar, Tengku Salman Fathi

    Published 2006
    “…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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    Multiview Laplacian semisupervised feature selection by leveraging shared knowledge among multiple tasks by Krishnasamy, Ganesh, Paramesran, Raveendran

    Published 2019
    “…Experiment results on several multimedia applications have shown that the proposed algorithm is competitive compared with the other single-view feature selection algorithms.…”
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    Article
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    Evaluation and optimization of frequent, closed and maximal association rule based classification by Mohd Shaharanee, Izwan Nizal, Hadzic, Fedja

    Published 2014
    “…Real world applications of association rule mining have well-known problems of discovering a large number of rules, many of which are not interesting or useful for the application at hand.The algorithms for closed and maximal item sets mining significantly reduce the volume of rules discovered and complexity associated with the task, but the implications of their use and important differences with respect to the generalization power, precision and recall when used in the classification problem have not been examined.In this paper, we present a systematic evaluation of the association rules discovered from frequent, closed and maximal item set mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriate sequence of usage.The experiments are performed using a number of real-world datasets that represent diverse characteristics of data/items, and detailed evaluation of rule sets is provided as a whole and w.r.t individual classes. …”
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    Framework for stream clustering of trajectories based on temporal micro clustering technique by Abdulrazzaq, Musaab Riyadh

    Published 2018
    “…The framework consists of two stages: the preprocessing stage and the stream clustering stage. …”
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