Abstract
Cases available in real world domains are often incomplete and sometimes lack important information. Using incomplete cases in a CBR system can be harmful, as the lack of information can result in inappropriate similarity computations or incompletely generated adaptation knowledge. Case completion aims to overcome this issue by inferring missing information. This paper presents a novel approach to case completion for process-oriented case-based reasoning (POCBR). In particular, we address the completion of workflow cases by adding missing or incomplete dataflow information. Therefore, we combine automatically learned domain specific completion operators with generic domain-independent default rules. The empirical evaluation demonstrates that the presented completion approach is capable of deriving complete workflows with high quality and a high degree of completeness.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
The terms completeness and consistency used here with respect to workflows must not be confused with the use of those terms within logics — here, we mean something different, as defined below.
- 2.
Within the same control-flow block.
- 3.
We omit the index if it is obvious which ontology is referenced.
References
Bach, K., Althoff, K.D., Satzky, J., Kroehl, J.: CookIIS mobile: a case-based reasoning recipe customizer for android phones. In: Petridis, M., Roth-Berghofer, T., Wiratunga, N. (eds.) Proceeding of UKCBR 2012, 11 December, Cambridge, United Kingdom, pp. 15–26. Engineering and Mathematics, University of Brighton, UK, School of Computing (2012)
Badra, F., Cordier, A., Lieber, J.: Opportunistic adaptation knowledge discovery. In: McGinty, L., Wilson, D.C. (eds.) ICCBR 2009. LNCS (LNAI), vol. 5650, pp. 60–74. Springer, Heidelberg (2009). doi:10.1007/978-3-642-02998-1_6
Bergmann, R., Gessinger, S., Görg, S., Müller, G.: The collaborative agile knowledge engine CAKE. In: Proceedings of the 18th International Conference on Supporting Group Work, pp. 281–284. ACM (2014)
Bergmann, R., Gil, Y.: Similarity assessment and efficient retrieval of semantic workflows. Inf. Syst. 40, 115–127 (2014)
Bergmann, R., Wilke, W., Vollrath, I., Wess, S.: Integrating general knowledge with object-oriented case representation and reasoning. In: Burkhard, H.D., Wess, S. (eds.) 4th German Workshop: Case-Based Reasoning - System Development and Evaluation, pp. 120–126. Humboldt-Universität Berlin, Informatik-Berichte Nr. 55 (1996)
Burkhard, H.: Case completion and similarity in case-based reasoning. Comput. Sci. Inf. Syst. 1(2), 27–55 (2004)
Craw, S., Wiratunga, N., Rowe, R.: Learning adaptation knowledge to improve case-based reasoning. Artif. Intell. 170(16–17), 1175–1192 (2006)
Davenport, T.: Process Innovation: Reengineering Work Through Information Technology. Harvard Business Review Press, Boston (2013)
Dufour-Lussier, V., Ber, F.L., Lieber, J., Nauer, E.: Automatic case acquisition from texts for process-oriented case-based reasoning. Inf. Syst. 40, 153–167 (2014)
Hanft, A., Schfer, O., Althoff, K.D.: Integration of drools into an OSGI-based BPM-platform for CBR. In: Minor, M., Montani, S., Recio-Garcia, J.A. (eds.) Workshop on Process-Oriented Case-Based Reasoning, ICCBR 2011, 19th, September 12–15, Greenwich, London, United Kingdom. University of Greenwich (2011)
Hanney, K., Keane, M.T.: The adaptation knowledge bottleneck: how to ease it by learning from cases. In: Leake, D.B., Plaza, E. (eds.) ICCBR 1997. LNCS, vol. 1266, pp. 359–370. Springer, Heidelberg (1997). doi:10.1007/3-540-63233-6_506
Koehler, J., Tirenni, G., Kumaran, S.: From business process model to consistent implementation: a case for formal verification methods. In: Proceedings of EDOC 2002, 17–20 September 2002, Lausanne, Switzerland, p. 96. IEEE Computer Society (2002)
Minor, M., Görg, S.: Acquiring adaptation cases for scientific workflows. In: Ram, A., Wiratunga, N. (eds.) ICCBR 2011. LNCS (LNAI), vol. 6880, pp. 166–180. Springer, Heidelberg (2011). doi:10.1007/978-3-642-23291-6_14
Minor, M., Montani, S., Recio-Garca, J.A.: Process-oriented case-based reasoning. Inf. Syst. 40, 103–105 (2014)
Müller, G., Bergmann, R.: Workflow streams: a means for compositional adaptation in process-oriented CBR. In: Lamontagne, L., Plaza, E. (eds.) ICCBR 2014. LNCS (LNAI), vol. 8765, pp. 315–329. Springer, Heidelberg (2014). doi:10.1007/978-3-319-11209-1_23
Müller, G., Bergmann, R.: CookingCAKE: a framework for the adaptation of cooking recipes represented as workflows. In: Kendall-Morwick, J. (ed.) Workshop Proceedings, ICCBR 2015, Frankfurt, Germany, 28–30 September 2015. CEUR Workshop Proceedings, vol. 1520, pp. 221–232 (2015). CEUR-WS.org
Müller, G., Bergmann, R.: Generalization of workflows in process-oriented case-based reasoning. In: Russell, I., Eberle, W. (eds.) Proceedings, FLAIRS 2015, Hollywood, Florida, 18–20 May 2015, pp. 391–396. AAAI Press (2015)
Müller, G., Bergmann, R.: Learning and applying adaptation operators in process-oriented case-based reasoning. In: Hüllermeier, E., Minor, M. (eds.) ICCBR 2015. LNCS (LNAI), vol. 9343, pp. 259–274. Springer, Heidelberg (2015). doi:10.1007/978-3-319-24586-7_18
Richter, M.M., Weber, R.O.: Case-Based Reasoning - A Textbook. Springer, Heidelberg (2013)
Roth-Berghofer, T.R.: Explanations and case-based reasoning: foundational issues. In: Funk, P., González Calero, P.A. (eds.) ECCBR 2004. LNCS (LNAI), vol. 3155, pp. 389–403. Springer, Heidelberg (2004). doi:10.1007/978-3-540-28631-8_29
Schumacher, P.: Workflow extraction from textual process descriptions. Dissertation, Johann Wolfgang Goethe Universität Frankfurt/Main (2016)
Schumacher, P., Minor, M., Schulte-Zurhausen, E.: Extracting and enriching workflows from text. In: IEEE 14th International Conference on Information Reuse & Integration, IRI 2013, San Francisco, CA, USA, 14–16 August 2013, pp. 285–292. IEEE (2013)
Schumacher, P., Minor, M., Walter, K., Bergmann, R.: Extraction of procedural knowledge from the web: a comparison of two workflow extraction approaches. In: Mille, A., Gandon, F.L., Misselis, J., Rabinovich, M., Staab, S. (eds.) Proceedings of WWW 2012, Lyon, France, 16–20 April 2012 (Companion Volume), pp. 739–747. ACM (2012)
Stahl, A.: Learning of Knowledge-Intensive Similarity Measures in Case-Based Reasoning. Dissertation, Technische Universität Kaiserslautern (2004)
Thaler, T., Dadashnia, S., Sonntag, A., Fettke, P., Loos, P.: The IWi process model corpus. Technical report, Institute for Information Systems (IWi) at the German Research Center for Artificial Intelligence (DFKI), October 2015
Trcka, N., van der Aalst, W.M.P., Sidorova, N.: Workflow completion patterns. In: IEEE Conference on Automation Science and Engineering, CASE 2009, Bangalore, India, 22–25 August 2011, pp. 7–12. IEEE (2009)
Wilke, W., Vollrath, I., Bergmann, R.: Using knowledge containers to model a framework for learning adaptation knowledge. In: Wettschereck, D., Aha, D.W. (eds.) ECML 1997. MLNet Workshop Notes - Case-Based Learning: Beyond Classification of Feature Vectors, pp. 68–75. NCARAI, Washington, D. C., USA (1997)
Acknowledgements
This work was funded by the German Research Foundation (DFG), project number BE 1373/3-1.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
Müller, G., Bergmann, R. (2016). Case Completion of Workflows for Process-Oriented Case-Based Reasoning. In: Goel, A., DÃaz-Agudo, M., Roth-Berghofer, T. (eds) Case-Based Reasoning Research and Development. ICCBR 2016. Lecture Notes in Computer Science(), vol 9969. Springer, Cham. https://doi.org/10.1007/978-3-319-47096-2_20
Download citation
DOI: https://doi.org/10.1007/978-3-319-47096-2_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-47095-5
Online ISBN: 978-3-319-47096-2
eBook Packages: Computer ScienceComputer Science (R0)