GCHL: A grid-clustering algorithm for high-dimensional very large spatial data bases
作者： A.H. Pilevar , M. Sukumar
DOI: 10.1016/J.PATREC.2004.09.052
关键词:
摘要: … GCHL like other density-based clustering methods can discover clusters of arbitrary shapes. … A density-based algorithm for discovering clusters in large spatial databases with noise. In: …
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Richard R. Muntz, Jiong Yang, Wei Wang, STING: A Statistical Information Grid Approach to Spatial Data Mining very large data bases. pp. 186- 195 ,(1997)
Raymond T. Ng, Jiawei Han, Efficient and Effective Clustering Methods for Spatial Data Mining very large data bases. pp. 144- 155 ,(1994)
Gholamhosein Sheikholeslami, Surojit Chatterjee, Aidong Zhang, WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases very large data bases. pp. 428- 439 ,(1998)
Aho AV, JE Hopcroft, JD Ullman, The Design and Analysis of Computer Algorithms ,(1974)
Alexander Hinneburg, Daniel A. Keim, An efficient approach to clustering in large multimedia databases with noise knowledge discovery and data mining. pp. 58- 65 ,(1998)
Hans-Peter Kriegel, Martin Ester, Jörg Sander, Xiaowei Xu, A density-based algorithm for discovering clusters in large spatial Databases with Noise knowledge discovery and data mining. pp. 226- 231 ,(1996)
Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopulos, Prabhakar Raghavan, Automatic subspace clustering of high dimensional data for data mining applications Proceedings of the 1998 ACM SIGMOD international conference on Management of data - SIGMOD '98. ,vol. 27, pp. 94- 105 ,(1998) , 10.1145/276304.276314
Eden W.M. Ma, Tommy W.S. Chow, A new shifting grid clustering algorithm Pattern Recognition. ,vol. 37, pp. 503- 514 ,(2004) , 10.1016/J.PATCOG.2003.08.014
Gautam Garai, B.B Chaudhuri, A novel genetic algorithm for automatic clustering Pattern Recognition Letters. ,vol. 25, pp. 173- 187 ,(2004) , 10.1016/J.PATREC.2003.09.012
Gautam Biswas, Richard C Dubes, Some experiments in two-dimensional grammatical inference Pattern Recognition Letters. ,vol. 2, pp. 173- 177 ,(1984) , 10.1016/0167-8655(84)90042-4