會議論文
| 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 | en |
| 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 | CHN |
| 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 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/18160 ) |