張忠義老師的歷程檔案

論文名稱	20080818--A Crossover-Imaged Clustering Algorithm with Bottom-Up Tree Architecture
發表日期	2008-08-18

[英文摘要] :
The grid-based clustering algorithms are efficient with low computation time, but the size of the predefined grids and the threshold of the significant cells are seriously influenced their effects. The ADCC [1] and ACICA+ [2] are two new grid-based clustering algorithms. The ADCC algorithm uses axis-shifted strategy and cell clustering twice to reduce the influences of the size of the cells and inherits the advantage with the low time complexity. And the ACICA+ uses the crossover image of significant cells and just only one cell clustering. But the extents of original significant cell in one crossover image are not easy to find what else clusters they belong to. The Crossover-imaged Clustering Algorithm with Bottom-up Tree Architecture, called CIC-BTA, is proposed to use bottom-up tree architecture to have the same results. The main idea of CIC-BTA algorithm is to use the bottom-up tree architecture to link the cells to be the pre-clusters and combine pre-clusters into one by using semi-significant cells The final set of clusters is the result.