Proceedings of the National Academy of Sciences, 99(12), pp. 7821–7826.
-
S. Goil, H. Nagesh, and A. Choudhary. MAFIA: Efficient and scalable subspace clus-tering for very large data sets. ACM KDD Conference, pp. 443–452, 1999.
-
D. W. Goodall. A new similarity index based on probability. Biometrics, 22(4), pp. 882–907, 1966.
708 BIBLIOGRAPHY
-
K. Gouda, and M. J. Zaki. Genmax: An efficient algorithm for mining maximal fre-quent itemsets. Data Mining and Knowledge Discovery, 11(3), pp. 223–242, 2005.
-
A. Goyal, F. Bonchi, and L. V. S. Lakshmanan. A data-based approach to social influence maximization. VLDB Conference, pp. 73–84, 2011.
-
A. Goyal, F. Bonchi, and L. V. S. Lakshmanan. Learning influence probabilities in social networks. ACM WSDM Conference, pp. 241–250, 2011.
-
R. Gozalbes, J. P. Doucet, and F. Derouin. Application of topological descriptors in QSAR and drug design: history and new trends. Current Drug Targets-Infectious Disorders, 2(1), pp. 93–102, 2002.
-
M. Gupta, J. Gao, C. Aggarwal, and J. Han. Outlier detection for temporal data. Morgan and Claypool, 2014.
-
S. Guha, R. Rastogi, and K. Shim. ROCK: A robust clustering algorithm for categor-ical attributes. Information Systems, 25(5), pp. 345–366, 2000.
-
S. Guha, R. Rastogi, and K. Shim. CURE: An efficient clustering algorithm for large databases. ACM SIGMOD Conference, pp. 73–84, 1998.
-
S. Guha, A. Meyerson, N. Mishra, R. Motwani, and L. O’Callaghan. Clustering data streams: Theory and practice. IEEE Transactions on Knowledge and Data Engineer-ing, 15(3), pp. 515–528, 2003.
-
D. Gunopulos, and G. Das. Time series similarity measures and time series indexing.
ACM SIGMOD Conference, pp, 624, 2001.
-
V. Guralnik, and G. Karypis. A scalable algorithm for clustering sequential data.
IEEE International Conference on Data Engineering, pp. 179–186, 2001.
-
V. Guralnik, and G. Karypis. Parallel tree-projection-based sequence mining algo-rithms. Parallel Computing, 30(4): pp. 443–472, April 2004. Also appears in European Conference in Parallel Processing, 2001.
-
D. Gusfield. Algorithms on strings, trees and sequences. Cambridge University Press, 1997.
-
I. Guyon (Ed.). Feature extraction: foundations and applications. Springer, 2006.
-
I. Guyon, and A. Elisseeff. An introduction to variable and feature selection. Journal of Machine Learning Research, 3, pp. 1157–1182, 2003.
-
M. Halkidi, Y. Batistakis, and M. Vazirgiannis. Cluster validity methods: part I. ACM SIGMOD record, 31(2), pp. 40–45, 2002.
-
M. Halkidi, Y. Batistakis, and M. Vazirgiannis. Clustering validity checking methods: part II. ACM SIGMOD Record, 31(3), pp. 19–27, 2002.
-
E. Han, and G. Karypis. Centroid-based document classification: analysis and exper-imental results. ECML Conference, pp. 424–431, 2000.
-
J. Han, M. Kamber, and J. Pei. Data mining: concepts and techniques. Morgan Kauf-mann, 2011.
Dostları ilə paylaş: |