Discovery of Sequential Patterns Based On Constraint Patterns
This paper proposes a method that discovers sequential patterns corresponding to user-s interests from sequential data. This method expresses the interests as constraint patterns. The constraint patterns can define relationships among attributes of the items composing the data. The method recursively decomposes the constraint patterns into constraint subpatterns. The method evaluates the constraint subpatterns in order to efficiently discover sequential patterns satisfying the constraint patterns. Also, this paper applies the method to the sequential data composed of stock price indexes and verifies its effectiveness through comparing it with a method without using the constraint patterns.
[1] R. Agrawal and R. Srikant, Mining Sequential Patterns, Proc. of the 11th
Intl. Conf. Data Engineering, 1995, Taipei, Taiwan, pp. 3-14.
[2] J. Ayres, J. Flannick, J. Gehrke, and T. Yiu, "Sequential pattern mining
using a bitmap representation," Proc. of the 8th Intl. Conf. on Knowledge
Discovery and Data Mining, 2002, Edmonton, Alberta, Canada, pp. 429-
435.
[3] M. N. Garofalakis, R. Rastogi, and K. Shim, "SPIRIT: Sequential Pattern
Mining with Regular Expression Constraints," Proc. of the Very Large
Data Bases Conf., 1999, Edinburgh, Scotland, UK, pp. 223-234.
[4] J. Pei, J. Han, B. Mortazavi-Asl, J. Wang, H. Pinto, Q. Chen, U. Dayal,
M. -C. Hsu, "Mining Sequential Patterns by Pattern-Growth: The PrefixSpan
Approach," IEEE Trans. on Knowledge and Data Engineering,
vol. 16, no. 11, pp. 1424-1440, 2004.
[5] J. Pei, J. Han, and W. Wang, "Mining Sequential Patterns with Constraints
in Large Databases," Proc. of the 11th ACM Intl. Conf. on Information
and Knowledge Management, 2002, McLean, Virginia, USA, pp. 18-25.
[6] S. Sakurai, K. Ueno, and R. Orihara, "Discovery of Time Series Event
Patterns based on Time Constraints from Textual Data," Intl. J. of
Computational Intelligence, vol. 4, no. 2, pp. 144-151, 2008.
[7] S. Sakurai, Y. Kitahara, R. Orihara, K. Iwata, N. Honda, and T. Hayashi,
"Discovery of Sequential Patterns Coinciding with Analysts- Interests,"
J. of Computers, vol. 3, issue 7, pp. 1-8, 2008.
[8] R. Srikant and R. Agrawal, "Mining Sequential Patterns: Generalizations
and Performance Improvements," Proc. of the 5th Intl. Conf. Extending
Database Technology, 1996, Avignon, France, pp. 3-17.
[9] Z. Yang and M. Kitsuregawa, "LAPIN-SPAM: An Improved Algorithm
for Mining Sequential Pattern," Proc. of the 21st Intl. Conf. on Data
Engineering Workshops, 2005, Tokyo, Japan, pp. 1222.
[10] M. J. Zaki, "SPADE: An Efficient Algorithm for Mining Frequent
Sequences," Machine Learning, vol. 42, no. 1/2, pp, 31-60, 2001.
[1] R. Agrawal and R. Srikant, Mining Sequential Patterns, Proc. of the 11th
Intl. Conf. Data Engineering, 1995, Taipei, Taiwan, pp. 3-14.
[2] J. Ayres, J. Flannick, J. Gehrke, and T. Yiu, "Sequential pattern mining
using a bitmap representation," Proc. of the 8th Intl. Conf. on Knowledge
Discovery and Data Mining, 2002, Edmonton, Alberta, Canada, pp. 429-
435.
[3] M. N. Garofalakis, R. Rastogi, and K. Shim, "SPIRIT: Sequential Pattern
Mining with Regular Expression Constraints," Proc. of the Very Large
Data Bases Conf., 1999, Edinburgh, Scotland, UK, pp. 223-234.
[4] J. Pei, J. Han, B. Mortazavi-Asl, J. Wang, H. Pinto, Q. Chen, U. Dayal,
M. -C. Hsu, "Mining Sequential Patterns by Pattern-Growth: The PrefixSpan
Approach," IEEE Trans. on Knowledge and Data Engineering,
vol. 16, no. 11, pp. 1424-1440, 2004.
[5] J. Pei, J. Han, and W. Wang, "Mining Sequential Patterns with Constraints
in Large Databases," Proc. of the 11th ACM Intl. Conf. on Information
and Knowledge Management, 2002, McLean, Virginia, USA, pp. 18-25.
[6] S. Sakurai, K. Ueno, and R. Orihara, "Discovery of Time Series Event
Patterns based on Time Constraints from Textual Data," Intl. J. of
Computational Intelligence, vol. 4, no. 2, pp. 144-151, 2008.
[7] S. Sakurai, Y. Kitahara, R. Orihara, K. Iwata, N. Honda, and T. Hayashi,
"Discovery of Sequential Patterns Coinciding with Analysts- Interests,"
J. of Computers, vol. 3, issue 7, pp. 1-8, 2008.
[8] R. Srikant and R. Agrawal, "Mining Sequential Patterns: Generalizations
and Performance Improvements," Proc. of the 5th Intl. Conf. Extending
Database Technology, 1996, Avignon, France, pp. 3-17.
[9] Z. Yang and M. Kitsuregawa, "LAPIN-SPAM: An Improved Algorithm
for Mining Sequential Pattern," Proc. of the 21st Intl. Conf. on Data
Engineering Workshops, 2005, Tokyo, Japan, pp. 1222.
[10] M. J. Zaki, "SPADE: An Efficient Algorithm for Mining Frequent
Sequences," Machine Learning, vol. 42, no. 1/2, pp, 31-60, 2001.
@article{"International Journal of Information, Control and Computer Sciences:59554", author = "Shigeaki Sakurai and Youichi Kitahata and Ryohei Orihara", title = "Discovery of Sequential Patterns Based On Constraint Patterns", abstract = "This paper proposes a method that discovers sequential patterns corresponding to user-s interests from sequential data. This method expresses the interests as constraint patterns. The constraint patterns can define relationships among attributes of the items composing the data. The method recursively decomposes the constraint patterns into constraint subpatterns. The method evaluates the constraint subpatterns in order to efficiently discover sequential patterns satisfying the constraint patterns. Also, this paper applies the method to the sequential data composed of stock price indexes and verifies its effectiveness through comparing it with a method without using the constraint patterns.
", keywords = "Sequential pattern mining, Constraint pattern, Attribute
constraint, Stock price indexes", volume = "2", number = "11", pages = "3876-7", }
