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[HKGT03] Hadjieleftheriou, M.; Kollios, G.; Gunopulos, D.; Tsotras, V.J., Online discovery of dense areas in spatio-temporal databases, In: Proc. 2003 Int. Symp. Spatial and Temporal Databases (SSTD’03) Santorini Island, Greece. (July 2003), pp. 306–324.

[HKKR99] Höppner, F.; Klawonn, F.; Kruse, R.; Runkler, T., Fuzzy Cluster Analysis: Methods for Classification, Data Analysis and Image Recognition. (1999) Wiley .

[HKP91] Hertz, J.; Krogh, A.; Palmer, R.G., Introduction to the Theory of Neural Computation. (1991) Addison-Wesley, Reading, MA .

[HLW07] Hsu, W.; Lee, M.L.; Wang, J., Temporal and Spatio-Temporal Data Mining. (2007) IGI Publishing .

[HLZ02] Hsu, W.; Lee, M.L.; Zhang, J., Image mining: Trends and developments, J. Intelligent Information Systems 19 (2002) 7–23.

[HMM86] Hong, J.; Mozetic, I.; Michalski, R.S., Incremental learning of attribute-based descriptions from examples, the method and user's guide, In: Report ISG 85-5, UIUCDCS-F-86-949 Department of Computer Science, University of Illinois at Urbana-Champaign. (1986).

[HMS66] Hunt, E.B.; Marin, J.; Stone, P.T., Experiments in Induction. (1966) Academic Press .

[HMS01] Hand, D.J.; Mannila, H.; Smyth, P., Principles of Data Mining (Adaptive Computation and Machine Learning). (2001) MIT Press, Cambridge, MA .

[HN90] Hecht-Nielsen, R., Neurocomputing. (1990) Addison-Wesley, Reading, MA .

[Hor08] Horak, R., Telecommunications and Data Communications Handbook. 2nd ed. (2008) Wiley-Interscience .

[HP07] Hua, M.; Pei, J., Cleaning disguised missing data: A heuristic approach, In: Proc. 2007 ACM SIGKDD Intl. Conf. Knowledge Discovery and Data Mining (KDD’07) San Jose, CA. (Aug. 2007), pp. 950–958.

[HPDW01] Han, J.; Pei, J.; Dong, G.; Wang, K., Efficient computation of iceberg cubes with complex measures, In: Proc. 2001 ACM-SIGMOD Int. Conf. Management of Data (SIGMOD’01) Santa Barbara, CA. (May 2001), pp. 1–12.

[HPS97] Hosking, J.; Pednault, E.; Sudan, M., A statistical perspective on data mining, Future Generation Computer Systems 13 (1997) 117–134.

[HPY00] Han, J.; Pei, J.; Yin, Y., Mining frequent patterns without candidate generation, In: Proc. 2000 ACM-SIGMOD Int. Conf. Management of Data (SIGMOD’00) Dallas, TX. (May 2000), pp. 1–12.

[HRMS10] Hay, M.; Rastogi, V.; Miklau, G.; Suciu, D., Boosting the accuracy of differentially-private queries through consistency, In: Proc. 2010 Int. Conf. Very Large Data Bases (VLDB’10) Singapore. (Sept. 2010), pp. 1021–1032.

[HRU96] Harinarayan, V.; Rajaraman, A.; Ullman, J.D., Implementing data cubes efficiently, In: Proc. 1996 ACM-SIGMOD Int. Conf. Management of Data (SIGMOD’96) Montreal, Quebec, Canada. (June 1996), pp. 205–216.

[HS05] Hellerstein, J.M.; Stonebraker, M., Readings in Database Systems. 4th ed. (2005) MIT Press, Cambridge, MA .

[HSG90] Harp, S.A.; Samad, T.; Guha, A., Designing application-specific neural networks using the genetic algorithm, In: (Editor: Touretzky, D.S.) Advances in Neural Information Processing Systems II Morgan Kaufmann. (1990), pp. 447–454.

[HT98] Hastie, T.; Tibshirani, R., Classification by pairwise coupling, Ann. Statistics 26 (1998) 451–471.

[HTF09] Hastie, T.; Tibshirani, R.; Friedman, J., The Elements of Statistical Learning: Data Mining, Inference, and Prediction. 2nd ed. (2009) Springer Verlag .

[Hua98] Huang, Z., Extensions to the k-means algorithm for clustering large data sets with categorical values, Data Mining and Knowledge Discovery 2 (1998) 283–304.

[Hub94] Huberty, C.H., Applied Discriminant Analysis. (1994) Wiley-Interscience .

[Hub96] Hubbard, B.B., The World According to Wavelets. (1996) A. K. Peters .

[HWB+04] Huan, J.; Wang, W.; Bandyopadhyay, D.; Snoeyink, J.; Prins, J.; Tropsha, A., Mining spatial motifs from protein structure graphs, In: Proc. 8th Int. Conf. Research in Computational Molecular Biology (RECOMB) San Diego, CA. (Mar. 2004), pp. 308–315.

[HXD03] He, Z.; Xu, X.; Deng, S., Discovering cluster-based local outliers, Pattern Recognition Lett. 24 (June, 2003) 1641