Probabilistic declarative process mining

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

Volumn 6291 LNAI, Issue , 2010, Pages 292-293

  Bellodi, Elena ^a   Riguzzi, Fabrizio ^a   Lamma, Evelina ^a  

^a UNIVERSITY OF FERRARA   (Italy)

Author keywords

Business Process Management; Knowledge based Process Models; Process Mining; Statistical Relational Learning

Indexed keywords

AUTOMATIC DISCOVERY; BUSINESS PROCESS; BUSINESS PROCESS MANAGEMENT; EFFICIENCY IMPROVEMENT; GRAPH-BASED; HIGH POTENTIAL; INTEGRITY CONSTRAINTS; KNOWLEDGE-BASED PROCESS; MARKOV LOGIC; PROBABILISTIC CLASSIFICATION; PROCESS EXECUTION; PROCESS MINING; PROCESS MODEL; REAL DATABASE; STATISTICAL RELATIONAL LEARNING; UNIVERSITY STUDENTS;

CHEMISTRY; DATA MINING; ENTERPRISE RESOURCE MANAGEMENT; KNOWLEDGE BASED SYSTEMS;

PROBABILISTIC LOGICS;

EID: 78049409671     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15280-1_28     Document Type: Conference Paper

References (21)

1. van der Aalst, W. M. P., van Dongen, B. F., Herbst, J., Maruster, L., Schimm, G., Weijters, A. J. M. M.: Workflow mining: A survey of issues and approaches. Data Knowledge Engineering 47(2), 237-267 (2003)
2. van der Aalst, W. M. P., Pesic, M.: A declarative approach for flexible business processes management. In: Eder, J., Dustdar, S. (eds.) BPM Workshops 2006. LNCS, vol. 4103, pp. 169-180. Springer, Heidelberg (2006)
3. van der Aalst, W. M. P., Pesic, M.: DecSerFlow: Towards a truly declarative service flow language. In: Bravetti, M., Núñez, M., Zavattaro, G. (eds.) WS-FM 2006. LNCS, vol. 4184, pp. 1-23. Springer, Heidelberg (2006)
4. van der Aalst, W. M. P., Weijters, T., Maruster, L.: Workflow mining: Discovering process models from event logs. IEEE Transactions on Knowledge and Data Engineering 16(9), 1128-1142 (2004)
5. Agrawal, R., Gunopulos, D., Leymann, F.: Mining process models from workflow logs. In: Schek, H.-J., Saltor, F., Ramos, I., Alonso, G. (eds.) EDBT 1998. LNCS, vol. 1377, pp. 469-483. Springer, Heidelberg (1998)
6. Alberti, M., Chesani, F., Gavanelli, M., Lamma, E., Mello, P., Torroni, P.: Verifiable agent interaction in abductive logic programming: The SCIFF framework. ACM Transactions on Computational Logic 9 (4) (2008)
7. *IA 2003. LNCS, vol. 2829, Springer, Heidelberg (2003)
8. Chesani, F., Lamma, E., Mello, P., Montali, M., Riguzzi, F., Storari, S.: Exploiting inductive logic programming techniques for declarative process mining. In: Jensen, K., van der Aalst, W. M. P. (eds.) Transactions on Petri Nets. LNCS, vol. 5460, pp. 278-295. Springer, Heidelberg (2009)
9. Chesani, F., Mello, P., Montali, M., Storari, S.: Towards a decserflow declarative semantics based on computational logic. Technical Report DEIS-LIA-07-002, DEIS, Bologna, Italy (2007)
10. Clark, K. L.: Negation as failure. In: Logic and Databases. Plenum Press, New York (1978)
11. De Raedt, L., Van Laer, W.: Inductive constraint logic. In: Zeugmann, T., Shinohara, T., Jantke, K. P. (eds.) ALT 1995. LNCS (LNAI), vol. 997, Springer, Heidelberg (1995)
12. Domingos, P., Kok, S., Lowd, D., Poon, H., Richardson, M., Singla, P.: Markov logic. In: De Raedt, L., Frasconi, P., Kersting, K., Muggleton, S. H. (eds.) Probabilistic Inductive Logic Programming. LNCS (LNAI), vol. 4911, pp. 92-117. Springer, Heidelberg (2008)
13. Georgakopoulos, D., Hornick, M. F., Sheth, A. P.: An overview of workflow management: From process modeling to workflow automation infrastructure. Distributed and Parallel Databases 3(2), 119-153 (1995)
14. Greco, G., Guzzo, A., Pontieri, L., Saccà, D.: Discovering expressive process models by clustering log traces. IEEE Transactions on Knowledge and Data Engineering 18(8), 1010-1027 (2006)
15. Lamma, E., Mello, P., Montali, M., Riguzzi, F., Storari, S.: Inducing declarative logic-based models from labeled traces. In: Alonso, G., Dadam, P., Rosemann, M. (eds.) BPM 2007. LNCS, vol. 4714, pp. 344-359. Springer, Heidelberg (2007)
16. Lamma, E., Mello, P., Riguzzi, F., Storari, S.: Applying inductive logic programming to process mining. In: Blockeel, H., Ramon, J., Shavlik, J., Tadepalli, P. (eds.) ILP 2007. LNCS (LNAI), vol. 4894, pp. 132-146. Springer, Heidelberg (2008)
17. Provost, F. J., Fawcett, T.: Robust classification for imprecise environments. Machine Learning 42(3), 203-231 (2001)
18. Raedt, L. D., Dehaspe, L.: Clausal discovery. Machine Learning 26 (2-3), 99-146 (1997)
19. Richardson, M., Domingos, P.: Markov logic networks. Machine Learning 62 (1-2), 107-136 (2006)
20. Silva, R., Zhang, J., Shanahan, J. G.: Probabilistic workflow mining. In: Grossman, R., Bayardo, R. J., Bennett, K. P. (eds.) Proceedings of the Eleventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 275-284. ACM, New York (2005)
21. Singla, P., Domingos, P.: Lifted first-order belief propagation. In: Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, AAAI 2008, pp. 1094-1099. AAAI Press, Menlo Park (2008)