1998 Fall EE 380L Data Mining

Unique # 15250


Primary References

1
Heikki Mannila. Methods and problems in data mining (a tutorial). In F. Afrati and P. Kolaitis, editors, Proceedings of International Conference on Database Theory (ICDT'97), pages 41--55, Delphi, Greece, January 1997.
2
Daryl Pregibon Clark Glymour, David Madigan and Padhraic Smyth. Statistical themes and lessons for data mining. In Proceedings of the Second International Conference on Knowledge Discovery and Data Mining, pages 25--42, 1996.
3
Ming-Syan Chen, Jiawei Han, and Philip S. Yu. Data mining: an overview from a database perspective. IEEE Trans. On Knowledge And Data Engineering, 8:866--883, December 1996.
4
Surajit Chaudhuri and Umeshwar Dayal. An overview of data warehousing and OLAP technology. ACM SIGMOD Record, March 1997.
5
N. Megiddo S. Sarawagi, R. Agrawal. Discovery-driven exploration of OLAP data cubes. In Proc. of the Sixth Int'l Conference on Extending Database Technology (EDBT), March 1998.
6
Daniel Barbara, William DuMouchel, Christos Faloustsos, Peter J. Haas, Joseph M. Hellerstein, Yannis Ioadnnidis, H. V. Jagadish, Theodore Johnson, Raymond Ng, Viswanath Poosala, Kenneth A. Ross, and Kenneth C. Servcik. The new jersey data reduction report. IEEE Bulletin of the Technical Committee on Data Engineering, 20(4):3--45, December 1997.
7
Ron Kohavi and George H. John. Wrappers for feature subset selection. Artificial Intelligence, (to appear).
8
Prabhakar Raghavan Rakesh Agrawal, Johannes Gehrke: Dimitrios Gunopulos. Automatic subspace clustering of high dimensional data for data mining applications. In Proc. of the ACM SIGMOD Int'l Conference on Management of Data, Seattle, Washington, June 1998.
9
P.D Turney. The management of context-sensitive features: A review of strategies. In Proceedings of the ICML-96 Workshop on Learning in Context-Sensitive Domains, Bari, Italy, July 1996.
10
Charu C. Aggarwal and Philip S. Yu. Mining large itemsets for association rules. IEEE Bulletin of the Technical Committee on Data Engineering, 21(1):23--31, March 1998.
11
L. R. Rainer and B. H. Juang. An introduction to hidden markov models. IEEE ASSP Magazine, pages 4--16, January 1986.
12
Padhraic Smyth, David Heckerman, and Michael I. Jordan. Probabilistic independence networks for hidden markov probability models. Neural Computation, 9(2):227--269, 1997.
13
J. H. Friedman. An overview of predictive learning and function approximation. In V. Cherkassky, J.H. Friedman, and H. Wechsler, editors, From Statistics to Neural Networks, Proc. NATO/ASI Workshop, pages 1--61. Springer Verlag, 1994.
14
C. E. Brodley and P. Smyth. Applying classification algorithms in practice. Statistics and Computing, 7, 1997.
15
S. M. Weiss and N. Indurkhya. Rule-based machine learning methods for functional prediction. JAIR, pages 383--403, 1995.
16
P. Smyth. Clustering sequences with Hidden Markov Models. In M.I. Jordan M.C. Mozer and T. Petsche, editors, Advances in Neural Information Processing Systems-9, pages 648--54. MIT Press, 1997.
17
H. Mannila, H. Toivonen, and A. I. Verkamo. Discovering Frequent Episodes in Sequences. In U. M. Fayyad and R. Uthurusamy, editors, Proceedings of the First International Conference on Knowledge Discovery and Data Mining (KDD-95), Montreal, Canada, August 1995. AAAI Press.
18
G. Das, D. Gunopulos, and H. Mannila. Finding similar time series. Lecture Notes in Computer Science, 1263:88--98, 1997.
19
R. Agrawal and R. Srikant. Mining sequential patterns: Generalizations and performance improvements. In Proc. of the Fifth Int'l Conference on Extending Database Technology (EDBT), Avignon, France, 1996.
20
Andreas Arning, Rakesh Agrawal, and Prabhakar Raghavan. A linear method for deviation detection in large databases. In Proc. of the 2nd Int'l Conference on Knowledge Discovery in Databases and Data Mining, pages 164--169, Portland, Oregon, August 1996.
21
George H. John and Pat Langley. Static versus dynamic sampling for data mining. In Evangelos Simoudis, Jia Wei Han, and Usama Fayyad, editors, Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), page 367. AAAI Press, 1996.