Abstract
Building a high quality case base for knowledge intensive Case-Based Reasoning (CBR) applications is expensive and time consuming, especially when it requires manual work from experienced knowledge engineers. This paper presents a clustering-based method for capturing cases in time series data within the oil well drilling domain. We present a novel method for automatically detecting and capturing predictive cases originally created by domain experts. The research presented is evaluated within Verdande’s DrillEdge, in which until today case capturing is an experience-driven and thoroughly manual process. Our findings show that this process can be partially automated and customizing an individual CBR application in a complex domain can be further developed.
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References
Aamodt, A., Plaza, E.: Case-based reasoning: Foundational issues, methodological variations, and system approaches. Artificial Intelligence Communications 7(1), 39–59 (1994)
Ankerst, M., Breunig, M.M., Kriegel, H.P., Sander, J.: OPTICS: ordering points to identify the clustering structure. ACM SIGMOD Record 28(2), 49–60 (1999)
Arshadi, N., Jurisica, I.: Data mining for case-based reasoning in high-dimensional biological domains. IEEE Trans. on Knowledge and Data Engineering 17(8), 1127–1137 (2005)
Bach, K., Althoff, K.-D., Newo, R., Stahl, A.: A case-based reasoning approach for providing machine diagnosis from service reports. In: Ram, A., Wiratunga, N. (eds.) ICCBR 2011. LNCS, vol. 6880, pp. 363–377. Springer, Heidelberg (2011)
Bergmann, R., Richter, M.M., Schmitt, S., Stahl, A., Vollrath, I.: Utility-oriented matching: A new research direction for case-based reasoning. In: Schnurr, H.P., Staab, S., Studer, R., Stumme, G., Sure, Y. (eds.) Professionel Knowledge Management (Proc. of the 9th German Workshop on Case-Based Reasoning, GWCBR 2001), pp. 264–274. Shaker-Verlag, Aachen (2001)
Cheng, Y.: Mean shift, mode seeking, and clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(8), 790–799 (1995)
Cummins, L., Bridge, D.: Maintenance by a committee of experts: The mace approach to case-base maintenance. In: McGinty, L., Wilson, D.C. (eds.) ICCBR 2009. LNCS (LNAI), vol. 5650, pp. 120–134. Springer, Heidelberg (2009)
Cummins, L., Bridge, D.: On dataset complexity for case base maintenance. In: Ram, A., Wiratunga, N. (eds.) ICCBR 2011. LNCS (LNAI), vol. 6880, pp. 47–61. Springer, Heidelberg (2011)
Delany, S.J.: The good, the bad and the incorrectly classified: Profiling cases for case-base editing. In: McGinty, L., Wilson, D.C. (eds.) ICCBR 2009. LNCS, vol. 5650, pp. 135–149. Springer, Heidelberg (2009)
Dufour-Lussier, V., Le Ber, F., Lieber, J., Nauer, E.: Automatic case acquisition from texts for process-oriented case-based reasoning. Information Systems 40 (2014)
Ester, M., Kriegel, H.P., Sander, J., Xu, X.: A density-based algorithm for discovering clusters in large spatial databases with noise. In: Second International Conference on Knowledge Discovery and Data Mining, pp. 226–231 (1996)
Farley, B.: From free-text repair action messages to automated case generation. In: Proceedings of AAAI 1999 Spring Symposium: AI in Equipment Maintenance and Support (1999)
Flinter, S., Keane, M.T.: On the automatic generation of case libraries by chunking chess games. In: Veloso, M., Aamodt, A. (eds.) ICCBR 1995. LNCS, vol. 1010, pp. 421–430. Springer, Heidelberg (1995)
Floyd, M.W., Esfandiari, B.: An active approach to automatic case generation. In: McGinty, L., Wilson, D.C. (eds.) ICCBR 2009. LNCS, vol. 5650, pp. 150–164. Springer, Heidelberg (2009)
Fornells, A., Armengol, E., Golobardes, E.: Explanation of a clustered case memory organization. In: Proceedings of the 2007 Conference on Artificial Intelligence Research and Development, pp. 153–160. IOS Press, Amsterdam (2007)
Fornells, A., Recio-García, J.A., Díaz-Agudo, B., Golobardes, E., Fornells, E.: Integration of a methodology for cluster-based retrieval in jColibri. In: McGinty, L., Wilson, D.C. (eds.) ICCBR 2009. LNCS, vol. 5650, pp. 418–433. Springer, Heidelberg (2009)
Gundersen, O.E.: Toward measuring the similarity of complex event sequences in real-time. In: Díaz Adudo, B., Watson, I. (eds.) ICCBR 2012. LNCS, vol. 7466, pp. 107–121. Springer, Heidelberg (2012)
Gundersen, O.E., Sørmo, F., Aamodt, A., Skalle, P.: A real-time decision support system for high cost oil-well drilling operations. In: Twenty-Fourth IAAI Conference. AAAI Publications (2012)
Luckham, D.C.: The Power of Events: An Introduction to Complex Event Processing in Distributed Enterprise Systems. Addison-Wesley Longman Publishing Co., Inc., Boston (2001)
Manzoor, J., Asif, S., Masud, M., Khan, M.J.: Automatic case generation for case-based reasoning systems using genetic algorithms. In: 2012 Third Global Congress on Intelligent Systems, pp. 311–314 (2012)
Patterson, D., Rooney, N., Galushka, M., Anand, S.S.: Towards dynamic maintenance of retrieval knowledge in cbr. In: Proceedings of the Fifteenth International Florida Artificial Intelligence Research Society Conference, pp. 126–131. AAAI Press (2002)
Ram, A.: Continuous case-based reasoning. Artificial Intelligence 90(1-2), 25–77 (1997)
Ram, A., Santamaria, J.C.: Multistrategy learning in reactive control systems for autonomous robotic navigation. Informatica 17, 347–369 (1993)
Roddick, J.F., Spiliopoulou, M.: A survey of temporal knowledge discovery paradigms and methods. IEEE Transactions on Knowlegde and Data Engineering 14(4), 750–767 (2002)
Smyth, B., Bonzano, A., Cunningham, P.: Using introspective learning to improve retrieval in CBR: A case study in air traffic control. In: Leake, D.B., Plaza, E. (eds.) ICCBR 1997. LNCS, vol. 1266, pp. 291–302. Springer, Heidelberg (1997)
Smyth, B., Keane, M.T.: Remembering To Forget A Competence-Preserving Case Deletion Policy for Case-Based Reasoning Systems, pp. 377–383. Springer, Heidelberg (1995)
Smyth, B., McKenna, E.: Modelling the Competence of Case-Bases. In: Smyth, B., Cunningham, P. (eds.) EWCBR 1998. LNCS (LNAI), vol. 1488, pp. 208–220. Springer, Heidelberg (1998)
Smyth, B., McKenna, E.: Building Compact Competent Case-Bases. In: Althoff, K.-D., Bergmann, R., Branting, L.K. (eds.) ICCBR 1999. LNCS (LNAI), vol. 1650, pp. 329–342. Springer, Heidelberg (1999)
Steinhaus, H.: Sur la division des corps matériels en parties. Bull. Acad. Pol. Sci., Cl. III 4, 801–804 (1957)
Vernet, D., Golobardes, E.: An unsupervised learning approach for case-based classifier systems. Expert Update. The Specialist Group on Artificial Intelligence 6(2), 37–42 (2003)
Zhang, H., Song, K.: Research and experiment on Affinity Propagation clustering algorithm. In: 2011 Second International Conference on Mechanic Automation and Control Engineering, pp. 5996–5999 (2011)
Zhou, H., Wang, P., Li, H.: Research on Adaptive Parameters Determination in DBSCAN Algorithm. Journal of Information and Computational Science 7, 1967–1973 (2012)
Zhu, J., Yang, Q., Columbia, B.: Remembering to Add: Competence-preserving Case-Addition Policies for Case-Base Maintenance Case-deletion Policies, pp. 234–241. Morgan Kaufmann Publishers Inc., San Francisco (1999)
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Bach, K., Gundersen, O.E., Knappskog, C., Öztürk, P. (2014). Automatic Case Capturing for Problematic Drilling Situations. In: Lamontagne, L., Plaza, E. (eds) Case-Based Reasoning Research and Development. ICCBR 2014. Lecture Notes in Computer Science(), vol 8765. Springer, Cham. https://doi.org/10.1007/978-3-319-11209-1_5
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DOI: https://doi.org/10.1007/978-3-319-11209-1_5
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