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Survey & Tutorial Papers
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Data Clustering: A review , Anil K. Jain and M. N. Murthy and P. J. Flynn. Pattern Recognition and Image Processing Lab, Department of Computer Science And Engineering, Michigan State University. [PDF]
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Tutorial: Clustering Techniques for Large Data Sets: From the Past to the Future. , A. Hinneburg and D. Keim. Tutorial Notes for ACM SIGKDD int. conf. on Knowledge Discovery and Data Mining, 1999", [PDF]
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Clustering Algorithms for Spatial Databases: A Survey , Erica Kolatch, Dept. of Computer Science, University of Maryland, College Park. [PDF]
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BIRCH
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BIRCH: An Efficient Data Clustering Method for Very Large Databases , T. Zhang, R. Ramakrishnan and M. Livny, In Proc. of ACM SIGMOD International Conferance on Management of Data, 1996. [PDF]
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BIRCH: A New Data Clustering Algorithm and Its Applications, T. Zhang, R. Ramakrishnan and M. Livny, Kluwer Academic Publishers, Boston. [PDF][Source Code] [local copy of the code]
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CURE
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CURE: An efficient algorithm for clustering large databases , , S. Guha, R. Rastogi and K. Shim, n Proceedings of ACM SIGMOD International Conference on Management of Data, pages 73--84, New York, 1998. ACM. [ Short version(PDF)] [ long version (PS)] [Source Code (provided by Eui-Hong (Sam) Han, Dept. of Comp. Science & Eng. Univ. of Minnesota; han@cs.umn.edu)]
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CLARANS
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Efficient and Effective Clustering Methods for Spatial Data Mining, , R. T. Ng and J. Han, 20th International Conference on Very Large Data Bases, September 12--15, 1994, Santiago, Chile proceeding. [ PDF]
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DBSCAN
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A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise, , Ester M., Kriegel H.-P., Sander J., Xu X., Proc. 2nd Int. Conf.on Knowledge Discovery and Data Mining (KDD′96), Portland, OR, 1996, pp. 226-231 [ PDF]
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ScaleKM and ScaleEM
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Scaling Clustering Algorithms to Large Databases , P. S. Bradley and Usama M. Fayyad and Cory Reina, Knowledge Discovery and Data Mining, 1998. [PDF]
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Scaling EM (Expectation-Maximization) Clustering to Large Databases, P. S. Bradley and Usama Fayyad and Cory Reina, Microsoft Research, Tech. Report MSR-TR-98-35. [PDF]
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MAFIA
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MAFIA: Efficient and scalable subspace clustering for very large data sets H. Nagesh S. Goil and A. Choudhary, Technical Report 9906-010, Northwestern University, June 1999. [PDF]
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CHAMELEON
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CHAMELEON: A Hierarchical Clustering Algorithm Using Dynamic Modeling. George Karypis and Eui-Hong (Sam) Han and Vipin Kumar. Computer Vol. 32, No. 8, 1999. [PDF]
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ROCK
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ROCK: a robust clustering algorithm for categorical attributes . S. Guha, R. Rastogi and K. Shim. In Proceedings of International Conference on Data Engineering, 1999. [PDF]
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WaveCluster
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WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases. Gholamhosein Sheikholeslami and Surojit Chatterjee and Aidong Zhang. Proc. 24th Int. Conf. Very Large Data Bases. [PDF]
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STING
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STING : A Statistical Information Grid Approach to Spatial Data Mining. Wei Wang and Jiong Yang and Richard R. Muntz. The {VLDB} Journal, 1997. [PDF]
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STING+: An Approach to Active Spatial Data Mining. Wei Wang and Jiong Yang and Richard R. Muntz. ICDE, 1999. [PDF]
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DENCLUE
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An Efficient Approach to Clustering in Multimedia Databases with Noise. Hinneburg A., Keim D.A. Proc. 4rd Int. Conf. on Knowledge Discovery and Data Mining, New York, AAAI Press, 1998. [PDF]
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OPTICS
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OPTICS: Ordering Points To Identify the Clustering Structure, . nkerst M., Breunig M. M., Kriegel H.-P., Sander J. Proc. ACM SIGMOD Int. Conf. on Management of Data (SIGMOD′99), Philadelphia, PA, 1999, pp. 49-60. [PDF]
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ENCLUS
Source Code:(Top) - BIRCH - CLIQUE Link Inactive Demo:(Top) - Robust & Competitive Clustering Demo 1 - Clustering Demo 2 Currently Down
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、转载请注明来处和原文作者。非常感谢。
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