On the effective clustering of multidimensional data sequences
暂无分享,去创建一个
[1] Hans-Peter Kriegel,et al. A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.
[2] Jiawei Han,et al. Efficient and Effective Clustering Methods for Spatial Data Mining , 1994, VLDB.
[3] Antonin Guttman,et al. R-trees: a dynamic index structure for spatial searching , 1984, SIGMOD '84.
[4] Dimitrios Gunopulos,et al. Automatic subspace clustering of high dimensional data for data mining applications , 1998, SIGMOD '98.
[5] Sudipto Guha,et al. CURE: an efficient clustering algorithm for large databases , 1998, SIGMOD '98.
[6] Deok-Hwan Kim,et al. Similarity search for multidimensional data sequences , 2000, Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073).
[7] Tian Zhang,et al. BIRCH: an efficient data clustering method for very large databases , 1996, SIGMOD '96.
[8] Clu-istos Foutsos,et al. Fast subsequence matching in time-series databases , 1994, SIGMOD '94.
[9] Christos Faloutsos,et al. VideoTrails: representing and visualizing structure in video sequences , 1997, MULTIMEDIA '97.