Abstract
This paper introduces our work regarding the mining of decision activity logs generated by the users of a decision support system-like environment. We will show that a DSS can be modified in order to become “decision-aware. If the system offers support for all the data and information needs of the decision maker, how the user interacts with the software can provide us with a new perspective over the implicit and explicit knowledge employed in the decision process, as well as the decision patterns and strategies used for that decisional situation. All this valuable information will be stored as activity logs. Those logs need to be mined in order to build a graphical representation of the decision process. As proof-of-concept we focus on the enterprise loan contracting decision situation. We will show some of the models we created using several process mining algorithms and our own approach. Based on those models, we argue the new insights we can provide into the decision making process and the knowledge that is now explained and depicted as diagrams.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
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 and Knowledge Engineering 47(2), 237–267 (2003)
van der Aalst, W.M.P., Weijters, A.J.M.M.: Process Mining. Computers in Industry 53(3), 231–244 (2004)
Rozinat, A., Wynn, M., van der Aalst, W.M.P., ter Hofstede, A.H.M., Fidge, C.: Workflow Simulation for Operational Decision Support. Data and Knowledge Engineering 68(9), 834–850 (2009)
van der Aalst, W.M.P., Nakatumba, J., Rozinat, A., Russell, N.: Business Process Simulation: How to get it right? In: vom Brocke, J., Rosemann, M. (eds.) International Handbook on Business Process Management. Springer, Berlin (2009)
Agrawal, R., Gunopulos, D., Leymann, F.: Mining Process Models from Work-flow Logs. In: Schek, H.-J., Saltor, F., Ramos, I., Alonso, G. (eds.) EDBT 1998. LNCS, vol. 1377, pp. 469–483. Springer, Heidelberg (1998)
Schimm, G.: Process Miner: A Tool for Mining Process Schemes from Event-based Data. In: Flesca, S., Greco, S., Leone, N., Ianni, G. (eds.) JELIA 2002. LNCS (LNAI), vol. 2424, pp. 525–528. Springer, Heidelberg (2002)
Herbst, J., Karagiannis, D.: Integrating Machine Learning and Workflow Management to Support Acquisition and Adaptation of Workflow Models. International Journal of Intelligent Systems in Accounting, Finance and Management 9, 67–92 (2000)
Wen, L., Wang, J., van der Aalst, W.M.P., Huang, B., Sun, J.: A Novel Approach for Process Mining Based on Event Types. Journal of Intelligent Information Systems 32(2), 163–190 (2009)
van der Aalst, W.M.P.: Using Process Mining to Generate Accurate and Interactive Business Process Maps. In: Abramowicz, A., Flejter, D. (eds.) BIS 2009 Workshops. LNBIP, vol. 37, pp. 1–14. Springer, Berlin (2009)
Rozinat, A., van der Aalst, W.M.P.: Decision Mining in ProM. In: Dustdar, S., Fiadeiro, J.L., Sheth, A.P. (eds.) BPM 2006. LNCS, vol. 4102, pp. 420–425. Springer, Heidelberg (2006)
Rozinat, A., de Medeiros, A.K.A., Gunther, C.W., Weijters, A.J.M.M., van der Aalst, W.M.P.: The Need for a Process Mining Evaluation Framework in Research and Practice. In: ter Hofstede, A.H.M., Benatallah, B., Paik, H.-Y. (eds.) BPM Workshops 2007. LNCS, vol. 4928, pp. 84–89. Springer, Heidelberg (2008)
Rozinat, A., de Medeiros, A.K.A., Gunther, C.W., Weijters, A.J.M.M., van der Aalst, W.M.P.: Towards an Evaluation Framework for Process Mining Algorithms. BPM Center Report BPM-07-06, BPMcenter.org (2007)
van der Aalst, W.M.P., Weijters, A.J.M.M., Maruster, L.: Workflow Mining: Discovering Process Models from Event Logs. IEEE Transactions on Knowledge and Data Engineering 16(9), 1128–1142 (2004)
Wen, L., Wang, J., Sun, J.G.: Detecting Implicit Dependencies Between Tasks from Event Logs. In: Zhou, X., Li, J., Shen, H.T., Kitsuregawa, M., Zhang, Y. (eds.) APWeb 2006. LNCS, vol. 3841, pp. 591–603. Springer, Heidelberg (2006)
Weijters, A.J.M.M., van der Aalst, W.M.P.: Rediscovering Workflow Models from Event-Based Data using Little Thumb. Integrated Computer-Aided Engineering 10(2), 151–162 (2003)
de Medeiros, A.K.A., Weijters, A.J.M.M., van der Aalst, W.M.P.: Genetic Process Mining: An Experimental Evaluation. Data Mining and Knowledge Discovery 14(2), 245–304 (2007)
Gunther, C.W., van der Aalst, W.M.P.: Fuzzy Mining: Adaptive Process Simplification Based on Multi-perspective Metrics. In: Alonso, G., Dadam, P., Rosemann, M. (eds.) BPM 2007. LNCS, vol. 4714, pp. 328–343. Springer, Heidelberg (2007)
Gaaloul, W., Baïna, K., Godart, C.: Towards mining structural workflow patterns. In: Andersen, K.V., Debenham, J., Wagner, R. (eds.) DEXA 2005. LNCS, vol. 3588, pp. 24–33. Springer, Heidelberg (2005)
Mendling, J.: Metrics for Business Process Models: Empirical Foundations of Verification, Error Prediction, and Guidelines for Correctness. In: Mendling, J. (ed.) Metrics for Process Models. LNBIP, vol. 6, pp. 103–133. Springer, Heidelberg (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Petrusel, R., Mican, D. (2010). Mining Decision Activity Logs. In: Abramowicz, W., Tolksdorf, R., Węcel, K. (eds) Business Information Systems Workshops. BIS 2010. Lecture Notes in Business Information Processing, vol 57. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15402-7_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-15402-7_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15401-0
Online ISBN: 978-3-642-15402-7
eBook Packages: Computer ScienceComputer Science (R0)