Multi-dimensional relational sequence mining

Fundamenta Informaticae

Volumn 89, Issue 1, 2008, Pages 23-43

  Esposito, Floriana ^a   Di Mauro, Nicola ^a   Basile, Teresa M A ^a   Ferilli, Stefano ^a  

^a UNIVERSITY OF BARI   (Italy)

Author keywords

Inductive Logic Programming; Multi relational sequence mining; Sequence analysis

Indexed keywords

BIOINFORMATICS; COMPUTER PROGRAMMING; DATA MINING; INFORMATION MANAGEMENT; KNOWLEDGE BASED SYSTEMS; KNOWLEDGE MANAGEMENT; LOGIC PROGRAMMING; QUERY LANGUAGES; WEATHER FORECASTING;

COMPLEX PATTERNS; FIRST ORDERS; INDUCTIVE LOGIC PROGRAMMING; KNOWLEDGE DISCOVERIES; MULTI-DIMENSIONAL; MULTI-RELATIONAL SEQUENCE MINING; MULTIPLE DIMENSIONS; ONE DIMENSIONS; RELATIONAL DATA MININGS; SEQUENCE ANALYSIS; SEQUENTIAL INFORMATIONS; SEQUENTIAL PATTERN MININGS; SEQUENTIAL PATTERNS; SPATIO TEMPORALS; TEMPORAL INFORMATIONS; USER PROFILING;

MINING;

EID: 58149479714     PISSN: 01692968     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (45)

1. Agrawal, R., Manilla, H., Srikant, R., Toivonen, H., Verkamo, A.: Fast discovery of association rules, in: Advances in Knowledge Discovery and Data Mining (U. Fayyad, G, Piatetsky-Shapiro, R Smyth, R. Ufhurusamy, Eds.), AAA1 Press, 1996, 307-328.
2. Agrawal, R., Srikant, R.: Mining sequential patterns, in: Proceedings of the Int. Conf on Data Engineering (ICDE95), 1995, 3-14.
3. Allen, J., Ferguson, G.: Actions and Events in Interval Temporal Logic, Technical Report TR521, University of Rochester Rochester, NY, USA, 1994.
4. de Amo, S., Furtado, D.: First-order temporal pattern mining with regular expression constraints, Data & Knowledge Engineering, 62(3), 2007, 401-420.
5. de Amo, S., Giacometti, A., Junior, W. P.: Mining First-Order Temporal Interval Patterns with Regular Expression Constraints, in: Proceedings of the 9th International Conference on Data Warehousing and Knowledge Discovery (I. Y Song, J. Eder, T. M. Nguyen, Eds.), vol. 4654 of LNCS, Springer, 2007, 459-469.
6. Bennett, B., Cohn, A. G., Wolter, F., Zakharyaschev, M.: Multi-Dimensional Modal Logic as a Framework for Spatio-Temporal Reasoning, Applied Intelligence, 17(3), 2002, 239-251.
7. Beyer, K. S., Ramakrishnan, R.: Bottom-Up Computation of Sparse and Iceberg CUBEs, in: Proceedings ACM SIGMOD International Conference on Management of Data (A. Delis, C. Faloutsos, S. Ghandeharizadeh, Eds.), ACM Press, 1999, 359-370.
8. Blocked, H., Dehaspe, L., Demoen, B., Janssens, G., Ramon, J., Vandecasteele, H.: Executing query packs in 1LP, in: Proceedings of the 10th International Conference on Inductive Logic Programming (J. Cussens, A. Frisch, Eds.), vol. 1866 of LNAI, Springer, 2000, 60-77.
9. Blocked, H., Fürnkranz, J., Prskawetz, A., Billari, F: Detecting temporal changes in event sequences: An application to demographic data, in: Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery (L. D. Raedt, A. Siebes, Eds.), vol. 2168, Springer, 2001,29-41.
10. Bratko, I.: Prolog programming for artificial intelligence, 3rd ed., Addison-Wesley Longman Publishing Co., 2001, ISBN 0-201-40375-7.
11. Dehaspe, L., Toivonen, H.: Discovery of frequent Datalog patterns, Data Mining and Knowledge Discovery, 3(1), 1999, 7-36.
12. Gardner, M.: The fantastic combinations of John Conway's new solitaire game "life", Scientific American, 2(223), October 1970, 120-123.
13. Garofalakis, M. N., Rastogi, R., Shim, K.: SPIRIT: Sequential Pattern Mining with Regular Expression Constraints, in: Proceedings of 25th International Conference on Very Large Data Bases (M. P. Atkinson, M. E. Orlowska, P. Valduriez, S. B. Zdonik, M. L. Brodie, Eds.), Morgan Kaufmann, 1999, 223-234.
14. Greenberg, S.: Using Unix: collected traces of 168 users, Research Report 88/333/45, Department of Computer Science, University of Calgary, Alberta, 1988.
15. Han, J., Pei, J., Yin, Y: Mining frequent patterns without candidate generation, in: Proceedings of the 2000 ACM SIGMOD international conference on Management of data, ACM, 2000, 1-12.
16. Harinarayan, V., Rajaraman, A., Ullman, J. D.: Implementing Data Cubes Efficiently, in: Proceedings of the 1996 ACM SIGMOD International Conference on Management of Data (H. V. Jagadish, I. S. Mumick, Eds.), ACM Press, 1996, 205-216.
17. Jacobs, N.: Relational Sequence Learning and User Modelling, Ph.D. Thesis, Department of Computer Science, K.U.Leuven, Leuven, Belgium, October 2004.
18. Jacobs, N., Blockeel, H.: From shell logs to shell scripts, in: Proceedings of the 11th International Conference on Inductive Logic Programming (C. Rouveirol, M. Sebag, Eds.), vol. 2157, Springer, 2001, 80-90.
19. Kamber, M., Han, J., Chiang, J.: Metarule-Guided Mining of Multi-Dimensional Association Rules Using Data Cubes, in: Proceeding of the 3rd International Conference on Knowledge Discovery and Data Mining, 1997, 207-210.
20. Kaplan, C. A., Fenwick, J., Chen, J.: Adaptive Hypertext Navigation Based On User Goals and Context, User Modeling and User-Adapted Interaction, 3(3), 1993, 193-220.
21. Kersting, K., Gärtner, T.: Fisher Kernels for Logical Sequences, in: Proceedings of the 15th European Conference on Machine Learning (J.-F. Boulicaut, F. Esposito, F. Giannotti, D. Pedreschi, Eds.), vol. 3201 of LNCS, Springer, 2004, 205-216.
22. Kersting, K., Raedt, L. D., Raiko, T: Logical Hidden Markov Models, Journal of Artificial Intelligence Research, 25, 2006, 425-456.
23. Kersting, K., Raiko, T: 'Say EM' for Selecting Probabilistic Models for Logical Sequences, in: Proceedings of the 21st Conference on Uncertainty in Artificial Intelligence (F. Bacchus, T. Jaakkola, Eds.), AUAI Press, 2005, 300-307.
24. Lavrac, N., Dzeroski, S.: Inductive Logic Programming: Techniques and Applications., Ellis Horwood, New York, 1994.
25. Lee, S., De Raedt, L.: Constraint based mining of first order sequences in SeqLog, in: Database Support for Data Mining Applications (R. Meo, P. Lanzi, M. Klemettinen, Eds.), vol. 2682 of LNCS, Springer, 2004, 155-176.
26. Lenat, D.: The Dimensions of Context-Space, Cycorp, 1998.
27. Liao, L., Patterson, D. J., Fox, D., Kautz, H. A.: Learning and inferring transportation routines, Artificial Intelligence, 171(5-6), 2007, 311-331.
28. Malerba, D., Lisi, F.: Discovering associations between spatial objects: An ilp application, in: Proceedings of the 11th International Conference on Inductive Logic Programming, vol. 2157 of LNCS, Springer, 2001, 156-166.
29. Masson, C., Jacquenet, F.: Mining frequent logical sequences with SPIRIT-LoG, in: Proceedings of the 12th International Conference on Inductive Logic Programming (S. Matwin, C. Sammut, Eds.), vol. 2583 of LNAI, Sringer, 2003, 166-181.
30. McCarthy, J., Hayes, P.: Some Philosophical Problems from the Standpoint of Artificial Intelligence, in: Machine Intelligence 4 (B. Meltzer, D. Michie, Eds.), Edinburgh University Press, 1969, 463-502.
31. Moyle, S., Muggleton, S.: Learning Programs in the Event Calculus, in: Proceedings of the 7th International Workshop on Inductive Logic Programming, Springer, 1997, 205-212.
32. Muggleton, S., De Raedt, L.: Inductive Logic Programming: Theory and Methods, Journal of Logic Programming, 19/20, 1994, 629-679.
33. Pei, J., Han, J., Mortazavi-Asl, B., Pinto, H., Chen, Q., Dayal, U., Hsu, M.-C: PrefixSpan: Mining Sequential Patterns Efficiently by Prefix-Projected Pattern Growth, Proceedings of the 17th International Conference on Data Engineering, 2001, 215-226.
34. Pei, P., Han, J., Wang, W.: Mining Sequential Patterns with Constraints in Large Databases, in: Proceedings of the 11th ACM International Conference on Information and Knowledge Management, 2002, 18-25.
35. Pinto, H., Han, J., Pei, J., Wang, K., Chen, Q., Dayal, U.: Multi-dimensional sequential pattern mining, in: Proceedings of the tenth international conference on Information and knowledge management, ACM Press, 2001, 81-88.
36. Popelínsky, L.: Knowledge Discovery in Spatial Data by Means of ILP, in: Proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery, Springer, 1998, 185-193.
37. Randell, C., Muller, H.: Context Awareness by Analysing Accelerometer Data, in: The Fourth International Symposium on Wearable Computers (B. MacIntyre, B. Iannucci, Eds.), IEEE Computer Society, 2000, ISBN 1530-0811, 175-176.
38. Rodríguez, J., Alonso, C, Böstrom, H.: Learning first order logic time series classifiers, in: Proceedings of the 10th International Workshop on Inductive Logic Programming (J. Cussens, A. Frisch, Eds.), Springer, 2000, 260-275.
39. Si, H., Kawahara, Y., Morikawa, H., Aoyama, T.: A Stochastic Approach for Creating Context-Aware Services based on Context Histories in Smart Home, in: Proceeding of the 3rd International Conference on Pervasive Computing, Exploiting Context Histories in Smart Environments, 2005, 37-41.
40. Siewiorek, D., Smailagic, A., Furukawa, J., Krause, A., Moraveji, N., Reiger, K., Shaffer, J., Wong, F. L.: SenSay: A Context-Aware Mobile Phone, in: Proceedings of the 7th IEEE International Symposium on Wearable Computers, IEEE, 2003, 248-249.
41. Souchon, N., Limbourg, Q., Vanderdonckt, J.: Task Modelling in Multiple Contexts of Use, in: Proceedings of the 9th International Workshop on Interactive Systems. Design, Specification, and Verification, Springer, 2002, ISBN 3-540-00266-9, 59-73.
42. Ullman, J.: Principles of Database and Knowledge-Base Systems, vol. I, Computer Science Press, 1988.
43. Yu, C.-C., Chen, Y.-L.: Mining Sequential Patterns from Multidimensional Sequence Data, IEEE Transactions on Knowledge and Data Engineering, 17(1), 2005, 136-140, ISSN 1041-4347.
44. Zaki, M.: SPADE: An efficient algorithm for mining frequent sequences, Machine Learning Journal: Special issue on Unsupervised Learning, 42(1/2), 2001, 31-60.
45. Zhao, Q., Bhowmick, S.: Sequential pattern mining: a survey, Technical report, Center for Advanced Information Systems, School of Computer Engineering, Nanyang Technological University, Singapore, 2003.