Databases Reference
In-Depth Information
[Dun03]
M. Dunham.
Data Mining: Introductory and Advanced Topics
. Prentice-Hall, 2003.
[DWB06]
I. Davidson, K. L. Wagstaff, and S. Basu. Measuring constraint-set utility for partitional
clustering algorithms. In
Proc. 10th European Conf. Principles and Practice of Knowledge
Discovery in Databases (PKDD'06)
, pp. 115-126, Berlin, Germany, Sept. 2006.
[Dwo06]
C. Dwork.
Differential privacy.
In
Proc.
2006 Int.
Col.
Automata, Languages and
Programming (ICALP)
, pp. 1-12, Venice, Italy, July 2006.
[DYXY07]
W. Dai, Q. Yang, G. Xue, and Y. Yu. Boosting for transfer learning. In
Proc. 24th Intl.
Conf. Machine Learning
, pp. 193-200, Corvallis, OR, June 2007.
[Ega75]
J. P. Egan.
Signal Detection Theory and ROC Analysis
. Academic Press, 1975.
[EK10]
D. Easley and J. Kleinberg.
Networks, Crowds, and Markets: Reasoning about a Highly
Connected World
. Cambridge University Press, 2010.
[Esk00]
E. Eskin. Anomaly detection over noisy data using learned probability distributions. In
Proc. 17th Int. Conf. Machine Learning (ICML'00)
, Stanford, CA, 2000.
[EKSX96]
M. Ester, H.-P. Kriegel, J. Sander, and X. Xu. A density-based algorithm for discovering
clusters in large spatial databases. In
Proc. 1996 Int. Conf. Knowledge Discovery and Data
Mining (KDD'96)
, pp. 226-231, Portland, OR, Aug. 1996.
[EKX95]
M. Ester, H.-P. Kriegel, and X. Xu. Knowledge discovery in large spatial databases: Focus-
ing techniques for efficient class identification. In
Proc. 1995 Int. Symp. Large Spatial
Databases (SSD'95)
, pp. 67-82, Portland, ME, Aug. 1995.
[Elk97]
C. Elkan. Boosting and naıve Bayesian learning. In
Technical Report CS97-557
, Dept.
Computer Science and Engineering, University of California at San Diego, Sept.
1997.
[Elk01]
C. Elkan. The foundations of cost-sensitive learning. In
Proc. 17th Intl. Joint Conf.
Artificial Intelligence (IJCAI'01)
, pp. 973-978, Seattle, WA, 2001.
[EN10]
R. Elmasri and S. B. Navathe.
Fundamentals of Database Systems
(6th ed.). Boston:
Addison-Wesley, 2010.
[Eng99]
L. English.
Improving Data Warehouse and Business Information Quality: Methods for
Reducing Costs and Increasing Profits
. John Wiley & Sons, 1999.
[ESAG02]
A. Evfimievski, R. Srikant, R. Agrawal, and J. Gehrke. Privacy preserving mining of asso-
ciation rules. In
Proc. 2002 ACM SIGKDD Int. Conf. Knowledge Discovery and Data
Mining (KDD'02)
, pp. 217-228, Edmonton, Alberta, Canada, July 2002.
[ET93]
B. Efron and R. Tibshirani.
An Introduction to the Bootstrap
. Chapman & Hall, 1993.
[FB74]
R. A. Finkel and J. L. Bentley. Quad-trees: A data structure for retrieval on composite
keys.
ACTA Informatica
, 4:1-9, 1974.
[FB08]
J. Friedman and E. P. Bogdan. Predictive learning via rule ensembles.
Ann. Applied
Statistics
, 2:916-954, 2008.
[FBF77]
J. H. Friedman, J. L. Bentley, and R. A. Finkel. An algorithm for finding best matches in
logarithmic expected time.
ACM Transactions on Math Software
, 3:209-226, 1977.
[FFF99]
M. Faloutsos, P. Faloutsos, and C. Faloutsos. On power-law relationships of the internet
topology. In
Proc. ACM SIGCOMM'99 Conf. Applications, Technologies, Architectures,
and Protocols for Computer Communication
, pp. 251-262, Cambridge, MA, Aug. 1999.
[FG02]
M. Fishelson and D. Geiger. Exact genetic linkage computations for general pedigrees.
Disinformation
, 18:189-198, 2002.
