Mining closed discriminative dyadic sequential patterns

ACM International Conference Proceeding Series

Volumn , Issue , 2011, Pages 21-32

  Lo, David ^a   Cheng, Hong ^b   Lucia, ^a  

^a SINGAPORE MANAGEMENT UNIVERSITY   (Singapore)

^b CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

PROGRAM DEBUGGING;

DATABASE STRUCTURES; DETECTION PROCESS; DUPLICATE BUG REPORTS; PROJECTED DATABASE; PROPERTY; SEARCH SPACES; SEQUENCE OF EVENTS; SEQUENCE PAIR; SEQUENTIAL DATA; SEQUENTIAL PATTERNS;

CLASSIFICATION (OF INFORMATION);

EID: 79953841371     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1951365.1951371     Document Type: Conference Paper

References (27)

1. Eclipse Bug Repository. https://bugs.eclipse.org/bugs/.
2. Mozilla Bug Repository. https://bugzilla.mozilla.org/.
3. OpenOffice Bug Repository. http://www.openoffice.org/issues/query.cgi.
4. R. Agrawal and R. Srikant. Fast algorithms for mining associationrules inlarge databases. In VLDB, 1994.
5. R. Agrawal and R. Srikant. Mining sequential patterns. In ICDE, 1995.
6. C.-C. Chang and C.-J. Lin. LIBSVM: a library for support vector machines, 2001. Software available at http://www.csie.ntu.edu.tw/~/cjlin/libsvm.
7. H. Cheng, X. Yan, J. Han, and C. Hsu. Discriminative frequent pattern analysis for effective classification. In ICDE, pages 716-725, 2007. (Pubitemid 47422075)
8. H. Cheng, X. Yan, J. Han, and P. Yu. Discriminative frequent pattern analysis for effective classification. In ICDE, 2008.
9. S. Cong, J. Han, and D. Padua. Parallel mining of closed sequential patterns. In KDD, 2005.
10. B. Ding, D. Lo, J. Han, and S.-C. Khoo. Efficient mining of closed repetitive gapped subsequences from a sequence database. In ICDE, 2009.
11. G. Dong and J. Li. Efficient mining of emerging patterns: Discovering trends and differences. In KDD, 1999.
12. C. Gao, J. Wang, Y. He, and L. Zhou. Efficient mining of frequent sequence generators. In WWW, 2008.
13. J. Hanand M. Kamber. Data Mining: Concepts and Techniques (2nd ed.). Morgan Kaufmann, 2006.
14. W. S. Jr. and E. White. The Elements of Style, 4th Ed. Longman.
15. D. Lo, H. Cheng, J. Han, S.-C. Khoo, and C. Sun. Classification of software behaviors for failure detection: a discriminative pattern mining approach. In KDD, 2009.
16. D. Lo, S.-C. Khoo, and J. Li. Mining and ranking generators of sequential patterns. In SDM, 2008.
17. D. Lo, S.-C. Khoo, and C. Liu. Efficient mining of iterative patterns for software specification discovery. In Proc. 2007 ACM SIGKDD Int. Conf. Knowledge Discovery in Databases (KDD'07), pages 460-469, SanJose, CA, Aug. 2007. (Pubitemid 350229231)
18. D. Lo, S.-C. Khoo, and L. Wong. Non-redundant sequential rules - theory and algorithm. Information Systems, 34(4-5):438-453, 2009.
19. P. Nakov and H. Ng. Improved statistical machine translation for resource-poor languages using related resource-rich languages. In EMNLP, pages 1358-1367, 2009.
20. J. Pei, J. Han, B. Mortazavi-Asl, H. Pinto, Q. Chen, U. Dayal, and M.-C. Hsu. Prefixspan: Mining sequential patterns efficiently by prefix-projected pattern growth. In ICDE, 2001.
21. J. Quinlan. C4.5: Programs for Machine Learning. Morgan Kaufmann, 1993.
22. C. Sun, D. Lo, X. Wang, J. Jiang, and S.-C. Khoo. A discriminative model approach for accurate duplicate bug report retrieval. In ICSE, pages 45-54, 2010.
23. T. Uno, T. Asai, Y. Uchida, and H. Arimura. Lcm ver. 2: Efficient mining algorithms for frequent/closed/maximal itemsets. In FIMI, 2004.
24. J. Wang and J. Han. Bide: Efficient mining of frequent closed sequences. In ICDE, 2004.
25. J. Wang, J. Han, and J. Pei. Closet+: searching for the best strategies for mining frequent closed itemsets. In KDD, pages 236-245, 2003.
26. X. Yan, H. Cheng, J. Han, and P. Yu. Mining significant graph patterns by leap search. In SIGMOD, 2008.
27. X. Yan, J. Han, and R. Afshar. Clospan: Mining closed sequential patterns in large databases. In SDM, 2003.