Constraint based mining of first order sequences in SeqLog

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2682, Issue , 2004, Pages 154-173

  Lee, Sau Dan ^a   De Raedt, Luc ^a  

^a UNIVERSITY OF FREIBURG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

INTELLIGENT DATABASES;

BACK-GROUND KNOWLEDGE; CONSTRAINT-BASED MINING; FIRST-ORDER SEQUENCES; INDUCTIVE DATABASE; LEVEL-WISE ALGORITHMS; LOGICAL LANGUAGE; REPRESENTATION LANGUAGES; SEQUENTIAL PATTERNS;

QUERY PROCESSING;

EID: 33746094907     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: None     Document Type: Article

References (24)

1. Agrawal, R., Srikant, R.: Mining sequential patterns. In Yu, P.S., Chen, A.L.P., eds.: Proc. 11th Int. Conf. Data Engineering, ICDE, IEEE Press (1995) 3-14
2. Srikant, R., Agrawal, R.: Mining sequential patterns: Generalizations and performance improvements. In Apers, P.M.G., Bouzeghoub, M., Gardarin, G., eds.: Proc. 5th Int. Conf. Extending Database Technology, EDBT. Volume 1057., Springer-Verlag (1996) 3-17
3. Mannila, H., Toivonen, H., Verkamo, A.I.: Discovering frequent episodes in sequences. In Fayyad, U.M., Uthurusamy, R., eds.: First International Conference on Knowledge Discovery and Data Mining (KDD-95). (1995)
4. Garofalakis, M.N., Rastogi, R., Shim, K.: SPIRIT: Sequential pattern mining with regular expression constraints. In: Proceedings of the 25th International Conference on Very Large Data Bases (VLDB '99), San Francisco, Morgan Kaufmann (1999) 223-234
5. Wang, K.: Discovering patterns from large and dynamic sequential data. Journal of Intelligent Information Systems 9 (1997) 33-56
6. Zaki, M.J.: Fast mining of sequential patterns in very large databases. Technical Report 668, Computer Science, University of Rochester, PO Box 270226, Rochester, NY 14627, U.S.A. (1997)
7. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules. In Bocca, J.B., Jarke, M., Zaniolo, C., eds.: Proc. 20th Int. Conf. Very Large Data Bases, VLDB, Morgan Kaufmann (1994) 487-499
8. Jacobs, N., Blockeel, H.: From shell logs to shell scripts. In Rouveirol, C., ed.: Proc. 11th International Conference, ILP 2001 (Lecture notes in computer science, 2157: Lecture notes in artificial intelligence), Strasbourg, France, Springer Verlag (2001) 80-90
9. Mannila, H., Toivonen, H.: Discovering generalized episodes using minimal occurrences. In Simoudis, E., Han, J.W., Fayyad, U., eds.: Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), AAAI Press (1996) 146
10. Kersting, K., Raiko, T., Kramer, S., De Raedt, L.: Towards discovering structural signatures of protein folds based on logical hidden markov models. In: Proceedings of the Pacific Symposium on Biocomputing (PSB-2003), Kauai, Hawaii, U.S.A. (2003)
11. Kramer, S., De Raedt, L., Helma, C.: Molecular feature mining in hiv data. In: KDD-2001: The Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Association for Computing Machinery (2001) ISBN: 158113391X.
12. Hirsh, H.: Theoretical underpinnings of version spaces. In: Proceedings of the Twelfth International Joint Conference on Artificial Intelligence (IJCAI91), Morgan Kaufmann Publishers (1991) 665-670
13. Mannila, H., Toivonen, H.: Levelwise search and borders of theories in knowledge discovery. Data Mining and Knowledge Discovery 1 (1997) 241-258
14. Bayardo, R.: Efficiently mining long patterns from databases. In: Proceedings of ACM SIGMOD Conference on Management of Data. (1998)
15. Mitchell, T.: Generalization as search. Artificial Intelligence 18 (1980) 203-226
16. De Raedt, L., Kramer, S.: The levelwise version space algorithm and its application to molecular fragment finding. In: IJCAI01: Seventeenth International Joint Conference on Artificial Intelligence. (2001)
17. Mellish, C.: The description identification algorithm. Artificial Intelligence (1990)
18. Nienhuys-Cheng, S.H., de Wolf, R.: Foundations of Inductive Logic Programming (Lecture Notes in Computer Science, 1228). Springer Verlag (1997)
19. Nijssen, S., Kok, J.N.: Faster association rules for multiple relations. In: IJCAI. (2001) 891-896
20. Dehaspe, L., Toivonen, H.: Discovery of frequent datalog patterns. Data Mining and Knowledge Discovery Journal 3 (1999)
21. Greenberg, S.: Using unix: Collected traces of 168 users. Research Report 88/333/45, Department of Computer Science, University of Calgary, Calgary, Canada. (1988)
22. Masson, C., Jacquenet, F.: Mining frequent logical sequences with spirit-log. In: Proc. 12th International Conference on Inductive Logic Programming, ILP 2002, Sydney, Australia (2002)
23. De Raedt, L.: A logical database mining query language. In: Proceedings ILP'00. Volume 1866 of LNCS., springer (2000) 78-92
24. Bonner, A.J., Mecca, G.: Sequence datalog: Declarative string manipulation in databases. In: Logic in Databases. (1996) 399-413