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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/37319


    Title: An Adaptable Deflect and Conquer Clustering Algorithm
    Authors: Lin, Nancy P.;Chang, Chung-I;Pan, Chao-lung
    Contributors: 淡江大學資訊工程學系;淡江大學軍訓室
    Keywords: Data Mining;Clustering Algorithm;Grid-based;Significant Cell;Deflected Grid
    Date: 2007-04
    Issue Date: 2010-01-11 13:02:38 (UTC+8)
    Publisher: World Scientific and Engineering Academy and Society (WSEAS)
    Abstract: The grid-based clustering algorithm is an efficient clustering algorithm, but the effect of the algorithm is seriously influenced by the size of the predefined grids and the threshold of the significant cells. Thus, in this paper, to reduce the influences of the size of the predefined grids and the threshold of the significant cells, we adopt deflect and conquer techniques to propose a new grid-based clustering algorithm, which is called Adaptable Deflect and Conquer Clustering (ADCC) algorithm. The idea of ADCC is to utilize the predefined grids and predefined threshold to identify the significant cells, by which nearby cells that are also significant can be merged to develop a cluster in the first place. Next, the modified grids which are deflected to half size of the grid are used to identify the significant cells again. Finally, the new generated significant cells and the initial significant cells are merged so as to offset the round-off error and improve the precision of clustering task. And we verify by experiment that the performance of our new grid-based clustering algorithm, ADCC, is good.
    Relation: Proceedings of the 6th WSEAS International Conference on Applied Computer Science (ACOS'07), pp.155-159
    Appears in Collections:[Graduate Institute & Department of Computer Science and Information Engineering] Proceeding
    [Office of Military Education and Training] Proceeding

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