Databases Reference
In-Depth Information
[HF94]
J. Han and Y. Fu. Dynamic generation and refinement of concept hierarchies for
knowledge discovery in databases. In Proc. AAAI'94 Workshop Knowledge Discovery in
Databases (KDD'94) , pp. 157-168, Seattle, WA, July 1994.
[HF95]
J. Han and Y. Fu. Discovery of multiple-level association rules from large databases. In
Proc. 1995 Int. Conf. Very Large Data Bases (VLDB'95) , pp. 420-431, Zurich, Switzerland,
Sept. 1995.
[HF96]
J. Han and Y. Fu. Exploration of the power of attribute-oriented induction in data
mining. In U. M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy (eds.),
Advances in Knowledge Discovery and Data Mining , pp. 399-421. AAAI/MIT Press, 1996.
[HFLP01]
P. S. Horn, L. Feng, Y. Li, and A. J. Pesce. Effect of outliers and nonhealthy individuals
on reference interval estimation. Clinical Chemistry , 47:2137-2145, 2001.
[HG05]
K. A. Heller and Z. Ghahramani. Bayesian hierarchical clustering. In Proc. 22nd Int.
Conf. Machine Learning (ICML'05) , pp. 297-304, Bonn, Germany, 2005.
[HG07]
A. Hinneburg and H.-H. Gabriel. DENCLUE 2.0: Fast clustering based on kernel den-
sity estimation. In Proc. 2007 Int. Conf. Intelligent Data Analysis (IDA'07) , pp. 70-80,
Ljubljana, Slovenia, 2007.
[HGC95]
D. Heckerman, D. Geiger, and D. M. Chickering. Learning Bayesian networks:
The combination of knowledge and statistical data. Machine Learning , 20:197-243,
1995.
[HH01]
R. J. Hilderman and H. J. Hamilton. Knowledge Discovery and Measures of Interest .
Kluwer Academic, 2001.
[HHW97]
J. Hellerstein, P. Haas, and H. Wang. Online aggregation. In Proc. 1997 ACM-
SIGMOD Int. Conf. Management of Data (SIGMOD'97) , pp. 171-182, Tucson, AZ, May
1997.
[Hig08]
R. C. Higgins.
Analysis for Financial Management with S&P Bind-In Card .
Irwin/
McGraw-Hill, 2008.
[HK91]
P. Hoschka and W. Klosgen. A support system for interpreting statistical data. In
G. Piatetsky-Shapiro and W. J. Frawley (eds.), Knowledge Discovery in Databases ,
pp. 325-346. AAAI/MIT Press, 1991.
[HK98]
A. Hinneburg and D. A. Keim. An efficient approach to clustering in large multimedia
databases with noise. In Proc. 1998 Int. Conf. Knowledge Discovery and Data Mining
(KDD'98) , pp. 58-65, New York, NY, Aug. 1998.
[HKGT03]
M. Hadjieleftheriou, G. Kollios, D. Gunopulos, and V. J. Tsotras. Online discovery of
dense areas in spatio-temporal databases. In Proc. 2003 Int. Symp. Spatial and Temporal
Databases (SSTD'03) , pp. 306-324, Santorini Island, Greece, July 2003.
[HKKR99]
F. Hoppner, F. Klawonn, R. Kruse, and T. Runkler. Fuzzy Cluster Analysis: Methods for
Classification, Data Analysis and Image Recognition . Wiley, 1999.
[HKP91]
J. Hertz, A. Krogh, and R. G. Palmer. Introduction to the Theory of Neural Computation .
Reading, MA: Addison-Wesley, 1991.
[HLW07]
W. Hsu, M. L. Lee, and J. Wang. Temporal and Spatio-Temporal Data Mining . IGI
Publishing, 2007.
[HLZ02]
W. Hsu, M. L. Lee, and J. Zhang. Image mining: Trends and developments. J. Intelligent
Information Systems , 19:7-23, 2002.
 
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