教師資料查詢 | 類別: 會議論文 | 教師: 張忠義 CHANG, CHUNG-I (瀏覽個人網頁)

標題:A Crossover-Imaged Clustering Algorithm with Bottom-Up Tree Architecture
學年97
學期1
發表日期2008/10/18
作品名稱A Crossover-Imaged Clustering Algorithm with Bottom-Up Tree Architecture
作品名稱(其他語言)
著者Chang, Chung-i; Lin, N.P.
作品所屬單位淡江大學軍訓室; 淡江大學資訊工程學系
出版者Institute of Electrical and Electronics Engineers(IEEE)
會議名稱Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on,pp327-331
會議地點Shandong, China
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 extension of original significant cell in one crossover image is not easy to find what else clusters it belongs 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 significant 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.
關鍵字Bottom-up tree;Crossover image;Data Mining;Grid-based clustering;Significant Cell
語言英文
收錄於
會議性質國際
校內研討會地點
研討會時間
通訊作者
國別中國
公開徵稿Y
出版型式20081018~20081020;紙本
出處Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on (Volume:2 ), pp.327-331
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