APSCAN: A parameter free algorithm for clustering

Pattern Recognition Letters - Tập 32 - Trang 973-986 - 2011
Xiaoming Chen1,2, Wanquan Liu2, Huining Qiu2,3, Jianhuang Lai1
1School of Information Science and Technology, Sun Yat-Sen University, Guangzhou 510275, PR China
2Department of Computing, Curtin University of Technology, Bentley, WA 6102, Australia
3School of Mathematics and Computational Science, Sun Yat-sen University, Guangzhou, 510275, PR China

Tài liệu tham khảo

Agrawal, R., Gehrke, J., Gunopulos, D., Raghavan, P., 1998. Automatic subspace clustering of high dimensional data for data mining applications. In: Proc. ACM SIGMOD Internat. Conf. on the Management of Data, pp. 94–105. Ben, 2002, Support vector clustering, J. Machine Learn. Res., 2, 125 Birant, 2007, ST-DBSCAN: An algorithm for clustering spatial-temporal data, Data Knowl. Eng., 60, 208, 10.1016/j.datak.2006.01.013 Castro, V.E., Yang, J., 2000. A fast and robust general purpose clustering algorithm. In: Proc. 6th Pacific Rim Internat. Conf. on Artificial Inetlligence, pp.208–218. Cristianini, N., Taylor, J.S., Kandola, J.S., 2001. Spectral kernel methods for clustering. In: NIPS 14, pp. 649–655. Dash, M., Liu, H., Xu, X., 2001. ‘1+1>2’: Merging distance and density based clustering. In: Proc. 7th Internat. Conf. on Database Systems for Advanced Application, pp. 32–39. Dueck, D., Frey, B.J., 2007. Non-metric affinity propagation for unsupervised image categortization. In: Proc. 11th Internat. Conf. on Computer Vision, pp.1–8. Ester, M., Kriegel, H.P., Sander, J., Xu, X.W., 1996. A density-based alogrithm for discovering clusters. In: Proc. Internat. Conf. on Very Large Databased, pp. 28–39. Everitt, 2001 Filippone, 2008, A survey of kernel and spectral methods for clustering, Pattern Recognition, 41, 176, 10.1016/j.patcog.2007.05.018 Forgy, 1965, Cluster analysis of multivariate data: Efficiency vs. interpretability of classifications, Biometrics, 21, 768 Frey, B.J., Dueck, D., 2005. Mixture modeling by affinity propagation. In: NIPS 18, pp. 379–386. Frey, 2007, Clustering by passing message between data points, Science, 315, 972, 10.1126/science.1136800 Girolami, 2002, Mercer kernel based clustering in feature space, IEEE Trans. Neural Networks, 13, 780, 10.1109/TNN.2002.1000150 Güting, 1994, An introduction to spatial database systems, J. VLDB, 3, 357, 10.1007/BF01231602 Hinneburg, A. Keim, D.A., 1998. An efficient approach to clustering in large multimedia databases with noise. In: Proc. 4th Internat. Conf. on Knowledge Discovery and Data Mining, pp. 58–65. Iwabuchi, 2002, Effects of cloud horiziontal inhomogeneity on the optical thickness retrieved from moderate-resolution satellites data, J. Atmos. Sci., 59, 2227, 10.1175/1520-0469(2002)059<2227:EOCHIO>2.0.CO;2 Jain, 2010, Data clustering: 50 years beyond K-means, Patter Recognition Lett., 31, 651, 10.1016/j.patrec.2009.09.011 Jain, 1988 Johnson, 1967, Hierarchical clustering scheme, Psychometrika, 32, 241, 10.1007/BF02289588 Kaufman, 1990 Kohonen, 1985, Median string, Pattern Recognition Lett., 3, 309, 10.1016/0167-8655(85)90061-3 Likas, 2003, The global K-means clustering algorithm, Pattern Recognition, 36, 451, 10.1016/S0031-3203(02)00060-2 Liu, 2008, Multi-modality video shot clustering with tensor representation, J. Multimed. Tools Appl., 41, 93, 10.1007/s11042-008-0220-5 MacQueen, J., 1967. Some methods for classification and analysis of multivariate observations. In: Proc: 5th Berkeley Symp., pp. 281–297. Sander, 1998, Density-based clustering in spatial databases: The alogrithm GDBSCAN and its applications, Data Min. Knowl. Disc., 2, 169, 10.1023/A:1009745219419 Schölkopf, 1998, Nonlinear component analysis as a kernel eigenvalue problem, Neural Comput., 10, 1299, 10.1162/089976698300017467 Spath, 1980 Viswanath, 2009, Rough-DBSCAN: A fast hybrid density based clustering method for large data sets, Pattern Recognition Lett., 30, 1477, 10.1016/j.patrec.2009.08.008 Viswanath, P., Pinkesh, R., 2006. l-DBSCAN: A fast hybrid density based clustering method. In: Proc. 18th Internat. Conf. on Pattern Recognition, pp. 912–915. Xu, 2005, Survey of clustering algorithms, IEEE Trans. Neural Network, 16, 645, 10.1109/TNN.2005.845141 Ye, Q.X., Wen, Gao., Zhang, W., 2003. Color image segmentation using density-based clustering. In: Proc. 28th IEEE Internat. Conf. on Acoustics, Speech, and Signal Processing, pp. 345–348. Zhang, X., Gao, J., Lu, P., Yan, Y.H., 2008. A novel speaker clustering algorithm via supervised affinity propagation. In: Proc. 33rd IEEE Internat. Conf. on Acoustics, Speech, and Signal Processing, pp. 245–248.