Heuristic methods for searching and clustering hierarchical workflows

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

Volumn 5717 LNCS, Issue , 2009, Pages 737-744

  Kastner, Michael ^a   Saleh, Mohamed Wagdy ^a   Wagner, Stefan ^a   Affenzeller, Michael ^a   Jacak, Witold ^a  

^a UNIVERSITY OF APPLIED SCIENCES UPPER AUSTRIA   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

EMERGENCY SERVICE; FIRE FIGHTING; RESCUE MISSIONS; WORK-FLOWS; WORKFLOW MODELS; WORKFLOW MODELING;

HEURISTIC METHODS; SYSTEM THEORY; EMERGENCY SERVICES; FIRE EXTINGUISHERS; FIRE FIGHTING EQUIPMENT;

MANAGEMENT; HEURISTIC METHODS;

EID: 78651243403     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04772-5_95     Document Type: Conference Paper

References (11)

1. Arlia, D., Coppola, M.: Experiments in parallel clustering with dbscan. In: Proceedings of the 7th International Euro-Par Conference Manchester on Parallel Processing, pp. 326-331. Springer, Heidelberg (2001)
2. Arthur, D., Vassilvitskii, S.: How Slow is the k-Means Method? In: Proceedings of the twenty-second annual symposium on Computational geometry, pp. 144-153. ACM Press, New York (2006)
3. Arthur, D., Vassilvitskii, S.: k-means++: The advantages of careful seeding. In: Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, pp. 1027-1035. Society for Industrial and Applied Mathematics (2007)
4. Borman, S.: The expectation maximization algorithm - a short tutorial (July 2004), http://www.seanborman.com/publications/
5. Dellaert, F.: The expectation maximization algorithm. Technical Report GITGVU- 02-20, Georgia Institute of Technology (February 2002)
6. Ester, M., Kriegel, H.P., Sander, J., Xu, X.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: Proceedings of 2nd International Conference on Knowledge Discovery and Data Mining, pp. 226-231. AAAI Press, Menlo Park (1996)
7. Fischer, L. (ed.): 2008 BPM & Workflow Handbook - Spotlight on Homan-Centric BPM, 1st edn. Future Strategies (2008)
8. Jung, J.-Y., Bae, J.: Workflow clustering method based on process similarity. In: Gavrilova, M.L., Gervasi, O., Kumar, V., Tan, C.J.K., Taniar, D., Laganá, A., Mun, Y., Choo, H. (eds.) ICCSA 2006. LNCS, vol. 3981, pp. 379-389. Springer, Heidelberg (2006)
9. Lundberg, J.: Principles of Workflow Support in Life Critical Situations. Blekinge Institute of Technology Licentiate Dissertion Series, vol. 2. Blekinge Institute of Technology (2007)
10. van der Aalst, W., van Hee, K.: Workflow Management: Models, Methods, and Systems. Cooperative Information Systems. MIT Press, Cambridge (2004)
11. Witten, I.H., Frank, E.: Data Mining: Practical machine learning tools and techniques, 2nd edn. Morgan Kaufmann, San Francisco (2005)