Bibliography

AIS93

R. Agrawal, T. Imielinski, and A. Swami.
Mining association rules between sets of items in large databases.
In Proc. of the ACM SIGMOD Conference on Management of Data, pages 207-216, Washington, D.C., May 1993. ACM.

AR00

Juan M. Ale and Gustavo H. Rossi.
An approach to discovering temporal association rules.
In Janice Carroll, Ernesto Damiani, Hisham Haddad, and David Oppenheim, editors, 2000 ACM Symposium on Applied Computing, volume 1, pages 294-300, Como, Italy, 2000. ACM.

AS94

R. Agrawal and R. Srikant.
Fast algorithms for mining association rules.
In Proc. of the 20th VLDB Conference, pages 487-499, Santiago, Chile, 1994.

BC95

D.J. Berndt and J. Clifford.
Finding patterns in time series: a dynamic programming approach.
In U.M. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy, editors, Advances in Knowledge Discovery and Data Mining, pages 229-248. AAAI Press/ MIT Press, 1995.

CP99

X. Chen and I. Petrounias.
Mining temporal features in association rules.
In J.M. Zytkow and J. Rauch, editors, 3rd European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'99), volume 1704 of Lecture Notes in Artificial Intelligence, pages 295-300, Prague, 1999. Springer.

DLM$^+$98

Gautam Das, King-Ip Lin, Heikki Mannila, Gopal Renganathan, and Padhraic Smyth.
Rule discovery from time series.
In Knowledge Discovery and Data Mining, pages 16-22, 1998.

Dun03

Margaret H. Dunham.
Data Mining, Introduction and Advanced Topics.
Pearson Education, Inc., 2003.
From the Southern Methodist University, Chapter 7, Web Mining, pp. 195-219, Chapter 9, Temporal Mining, pp. 245-273.

FLYH99

L. Feng, H. Lu, J. X. Yu, and J. Han.
Mining inter-transaction associations with templates.
In Proceedings of the 1999 ACM CIKM International Conference on Information and Knowledge Management, Kansas City, Missouri, USA, November 2-6, 1999, pages 225-233. ACM, 1999.

FM94

M. Ranganathan Faloutsos and Y. Manolopoulos.
Fast subsequence matching in time-series databases.
In Proc. ACM SIGMOD, pages 419-429, Minneapolis, MN, May 1994.

FW00

E. Frank and I. H. Witten.
Data Mining.
Morgan Kaufmann Publishers, 2000.
From the University of Waikato, New Zealand.

Hal00

Tara Halwes.
Transform-based similarity methods for sequence mining.
Undergraduate Graduation Project (MQP). Worcester Polytechnic Institute, Aug. 2000.
Winner, Provost's MQP Award for Computer Science.

Lai93

P. Laird.
Identifying and using patterns in sequential data.
In Klaus P. Jantke, Shigenobu Kobayashi, Etsuji Tomita, and Takashi Yokomori, editors, Algorithmic Learning Theory, 4th International Workshop, ALT '93, Tokyo, Japan, November 8-10, 1993, Proceedings, Lecture Notes in Computer Science, pages 1-18, Tokyo, Japan, 1993. Springer.

MTV95

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, 1995. AAAI Press.

RMS98

Sridhar Ramaswamy, Sameer Mahajan, and Abraham Silberschatz.
On the discovery of interesting patterns in association rules.
In Ashish Gupta, Oded Shmueli, and Jennifer Widom, editors, VLDB'98, Proceedings of 24rd International Conference on Very Large Data Bases, August 24-27, 1998, New York City, New York, USA, pages 368-379. Morgan Kaufmann, 1998.

SA96

R. Srikant and R Agrawal.
Mining sequential patterns: Generalizations and performance improvements.
In Proc. of the Fifth Int'l Conference on Extending Database Technology (EDBT), Avignon, France, March 1996.

Sho01

C.A. Shoemaker.
Mining association rules from set-valued data.
Master's thesis, Department of Computer Science, Worcester Polytechnic Institu te, May 2001.

SS02

Z. Stoecker-Sylvia.
A robust association rule mining tool for complex data.
Undergraduate Graduation Project (MQP). Worcester Polytechnic Institute, April 2002.

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