Small screen detected. You are viewing the mobile version of SlideWiki. If you wish to edit slides you will need to use a larger device.
R. Agrawal, J. Gehrke, D. Gunopulos, and P. Raghavan. Automatic subspace clustering of high dimensional data for data mining applications. SIGMOD’98
C. C. Aggarwal, C. Procopiuc, J. Wolf, P. S. Yu, and J.-S. Park. Fast algorithms for projected clustering. SIGMOD’99
S. Arora, S. Rao, and U. Vazirani. Expander flows, geometric embeddings and graph partitioning. J. ACM, 56:5:1–5:37, 2009.
J. C. Bezdek. Pattern Recognition with Fuzzy Objective Function Algorithms. Plenum Press, 1981.
K. S. Beyer, J. Goldstein, R. Ramakrishnan, and U. Shaft. When is ”nearest neighbor” meaningful? ICDT’99
Y. Cheng and G. Church. Biclustering of expression data. ISMB’00
I. Davidson and S. S. Ravi. Clustering with constraints: Feasibility issues and the k-means algorithm. SDM’05
I. Davidson, K. L. Wagstaff, and S. Basu. Measuring constraint-set utility for partitional clustering algorithms. PKDD’06
C. Fraley and A. E. Raftery. Model-based clustering, discriminant analysis, and density estimation. J. American Stat. Assoc., 97:611–631, 2002.
F. H¨oppner, F. Klawonn, R. Kruse, and T. Runkler. Fuzzy Cluster Analysis: Methods for Classification, Data Analysis and Image Recognition. Wiley, 1999.
G. Jeh and J. Widom. SimRank: a measure of structural-context similarity. KDD’02
H.-P. Kriegel, P. Kroeger, and A. Zimek. Clustering high dimensional data: A survey on subspace clustering, pattern-based clustering, and correlation clustering. ACM Trans. Knowledge Discovery from Data (TKDD), 3, 2009.
U. Luxburg. A tutorial on spectral clustering. Statistics and Computing, 17:395–416, 2007