基于模糊最近邻的高维数据聚类

[1] OPTICS: ordering points to indentify the clustering structure. Ankerst M,Breuning M,et al. In: SIGMOD’ 99,Philadelphia, PA . 1999

[2] Efficient and effective clustering method for spatial data mining. Ng R,Han J. In: the 20th VLDB Conference,Santiago, Chile . 1994

[3] Incremental clusters in large spatial databases. Ester M,Kriegel H P,et al. In: KDD’ 96, Portland, Oregon . 1996

[4] Automatic sub-space clustering of high dimensional data for data mining applications. Agrawal R,Gehrke J,et al. In:SIGMOD’ 98, Seatle, WA . 1998

[5] What is the nearest neighbor in high dimensional spaces?. Hinnebrug A,Aggarwal C,Keim D A. In: VLDB-2000,Cairo, Egypt . 2000

[6] Optimal grid-clustering: towards breaking the curse of dimensionality in high-dimensional clustering. Hinnebrug A,KeimA D. In: VLDB-1999, Edinbrugh, Scotland . 1999

[7] STING: A statistical information grid approach to spatial data minig. Zhang W,Yang J,Muntz R. In: VLDB’ 97, Athens,Greece . 1997

[1] OPTICS: ordering points to indentify the clustering structure. Ankerst M,Breuning M,et al. In: SIGMOD’ 99,Philadelphia, PA . 1999

[2] Efficient and effective clustering method for spatial data mining. Ng R,Han J. In: the 20th VLDB Conference,Santiago, Chile . 1994

[3] Incremental clusters in large spatial databases. Ester M,Kriegel H P,et al. In: KDD’ 96, Portland, Oregon . 1996

[4] Automatic sub-space clustering of high dimensional data for data mining applications. Agrawal R,Gehrke J,et al. In:SIGMOD’ 98, Seatle, WA . 1998

[5] What is the nearest neighbor in high dimensional spaces?. Hinnebrug A,Aggarwal C,Keim D A. In: VLDB-2000,Cairo, Egypt . 2000

[6] Optimal grid-clustering: towards breaking the curse of dimensionality in high-dimensional clustering. Hinnebrug A,KeimA D. In: VLDB-1999, Edinbrugh, Scotland . 1999

[7] STING: A statistical information grid approach to spatial data minig. Zhang W,Yang J,Muntz R. In: VLDB’ 97, Athens,Greece . 1997