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Case Based Representation and Retrieval with Time Dependent Features

  • Conference paper
Case-Based Reasoning Research and Development (ICCBR 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3620))

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Abstract

The temporal dimension of the knowledge embedded in cases has often been neglected or oversimplified in Case Based Reasoning systems. However, in several real world problems a case should capture the evolution of the observed phenomenon over time. To this end, we propose to represent temporal information at two levels: (1) at the case level, if some features describe parameters varying within a period of time (which corresponds to the case duration), and are therefore collected in the form of time series; (2) at the history level, if the evolution of the system can be reconstructed by retrieving temporally related cases.

In this paper, we describe a framework for case representation and retrieval able to take into account the temporal dimension, and meant to be used in any time dependent domain. In particular, to support case retrieval, we provide an analysis of similarity-based time series retrieval techniques; to support history retrieval, we introduce possible ways to summarize the case content, together with the corresponding strategies for identifying similar instances in the knowledge base. A concrete application of our framework is represented by the system RHENE, which is briefly sketched here, and extensively described in [20].

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References

  1. Aamodt, A., Plaza, E.: Case-based reasoning: foundational issues, methodological variations and systems approaches. AI Communications 7, 39–59 (1994)

    Google Scholar 

  2. Agrawal, R., Faloutsos, C., Swami, A.N.: Efficient similarity search in sequence databases. In: Lomet, D. (ed.) Proc. 4th Int. Conf. of Foundations of Data Organization and Algorithms, pp. 69–84. Springer, Berlin (1993)

    Google Scholar 

  3. Allen, J.F.: Towards a general theory of action and time. Artificial Intelligence 23, 123–154 (1984)

    Article  MATH  Google Scholar 

  4. Bellazzi, R., Larizza, C., Magni, P., Bellazzi, R.: Temporal data mining for the quality assessment of a hemodialysis service. Artificial Intelligence in Medicine (in press)

    Google Scholar 

  5. Bellazzi, R., Larizza, C., Magni, P., Montani, S., Stefanelli, M.: Intelligent analysis of clinical time series: an application in the diabetes mellitus domain. Artificial Intelligence in Medicine 20, 37–57 (2000)

    Article  Google Scholar 

  6. Bellazzi, R., Larizza, C., Riva, A.: Temporal abstractions for interpreting diabetic patients monitoring data. Intelligent Data Analysis 2, 97–122 (1998)

    Article  Google Scholar 

  7. Berchtold, S., Keim, D.A., Kriegel, H.P.: The x-tree: an index structure for high-dimensional data. In: Proc. VLDB 1996, pp. 28–39. Morgan Kaufman, San Mateo (1996)

    Google Scholar 

  8. Bichindaritz, I., Conlon, E.: Temporal knowledge representation and organization for case-based reasoning. In: Proc. TIME 1996, pp. 152–159. IEEE Computer Society Press, Washington (1996)

    Google Scholar 

  9. Chan, K.P., Fu, A.W.C.: Efficient time series matching by wavelets. In: Proc. ICDE 1999, pp. 126–133. IEEE Computer Society Press, Washington (1999)

    Google Scholar 

  10. Fuch, B., Mille, A., Chiron, B.: Operator decision aiding by adaptation of supervision strategies. In: Case-Based Reasoning Research and Development. LNCS (LNAI), pp. 23–32. Springer, Berlin (1995)

    Chapter  Google Scholar 

  11. Guttman, A.: R-trees: a dynamic index structure for spatial searching. In: Proc. ACM SIGMOD, pp. 47–57. ACM Press, New York (1984)

    Google Scholar 

  12. Hetland, M.L.: A survey of recent methods for efficient retrieval of similar time sequences. In: Bunke, H., Last, M., Kandel, A. (eds.) Data Mining in Time Series Databases. World Scientific, London (2003)

    Google Scholar 

  13. Jaczynski, M.: A framework for the management of past experiences with time-extended situations. In: Proc. ACM conference on Information and Knowledge Management (CIKM) 1997, pp. 32–38. ACM Press, New York (1997)

    Google Scholar 

  14. Jaere, M.D., Aamodt, A., Skalle, P.: Representing temporal knowledge for case-based prediction. In: Craw, S., Preece, A.D. (eds.) ECCBR 2002. LNCS (LNAI), vol. 2416, pp. 174–188. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  15. Jagadish, H.V., Mendelzon, A.O., Milo, T.: Similarity based queries. In: Proc. 14th ACM Symp. on Principles of Database Systems, San Jose, CA (1995)

    Google Scholar 

  16. Keogh, E.: Fast similarity search in the presence of longitudinal scaling in time series databases. In: Proc. Int. Conf. on Tools with Artificial Intelligence, pp. 578–584. IEEE Computer Society Press, Washington (1997)

    Chapter  Google Scholar 

  17. Keogh, E., Chakrabarti, K., Pazzani, M., Mehrotra, S.: Dimensionality reduction for fast similarity search in large time series databases. Knowledge and Information Systems 3(3), 263–286 (2000)

    Article  Google Scholar 

  18. Keravnou, E.T.: Modeling medical concepts as time objects. In: Wyatt, J.C., Stefanelli, M., Barahona, P. (eds.) AIME 1995. LNCS (LNAI), vol. 934, pp. 67–90. Springer, Heidelberg (1995)

    Google Scholar 

  19. Ma, J., Knight, B.: A framework for historical case-based reasoning. In: Ashley, K.D., Bridge, D.G. (eds.) ICCBR 2003. LNCS, vol. 2689, pp. 246–260. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  20. Montani, S., Portinale, L., Bellazzi, R., Leonardi, G.: Rhene: a case retrieval system for hemodialysis cases with dynamically monitored parameters. In: Funk, P., González Calero, P.A. (eds.) ECCBR 2004. LNCS (LNAI), vol. 3155, pp. 659–672. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  21. Nakhaeizadeh, G.: Learning prediction from time series: a theoretical and empirical comparison of cbr with some other approaches. In: EWCBR 1993. LNCS (LNAI), vol. 837, pp. 65–76. Springer, Berlin (1994)

    Google Scholar 

  22. Oppenheim, A.V., Shafer, R.W.: Digital signal processing. Prentice Hall, London (1975)

    MATH  Google Scholar 

  23. Patterson, D., Galushka, M., Rooney, N.: An effective indexing and retrieval approach for temporal cases. In: Proc. 17th FLAIRS 2004. AAAI Press, Miami (2004)

    Google Scholar 

  24. Ram, A., Santamaria, J.C.: Continuous case-based reasoning. In: Proc. AAAI Case-Based Reasoning Workshop, pp. 86–93 (1993)

    Google Scholar 

  25. Ritter, F.E., Larkin, J.H.: Developing process models as summaris of hci action sequences. Human Computer Interaction 9, 345–383 (1994)

    Article  Google Scholar 

  26. Rougegrez, S.: Similarity evaluation between observed behaviours for the prediction of processes. In: Topics in Case-Based Reasoning. LNCS (LNAI), vol. 837, pp. 155–166. Springer, Berlin (1994)

    Google Scholar 

  27. Schmidt, R., Heindl, B., Pollwein, B., Gierl, L.: Abstraction of data and time for multiparametric time course prognoses. In: Advances of Case-Based Reasoning. LNCS (LNAI), vol. 1168, pp. 377–391. Springer, Berlin (1996)

    Chapter  Google Scholar 

  28. Shahar, Y.: A framework for knowledge-based temporal abstractions. Artificial Intelligence 90, 79–133 (1997)

    Article  MATH  Google Scholar 

  29. Sollenborn, M., Nilsson, M.: Building a case-base for stress diagnosis: an analysis of classified respiratory sinus arrhythmia sequences. In: Proc. Case-Based Reasoning in the Health Sciences Workshop, European Conference on Case Based Reasoning, ECCBR (2004)

    Google Scholar 

  30. Stephen, G.A.: String searching algorithms. Lecture Notes Series in Computing, vol. 3. World Scientific, Singapore (1994)

    MATH  Google Scholar 

  31. Subrahmanian, V.S.: Principles of Multimedia Database Systems. Morgan Kaufmann, San Mateo (1998)

    Google Scholar 

  32. Ukkonen, E.: Algorithms for approximate string matching. Information Control 64, 100–118 (1985)

    Article  MATH  MathSciNet  Google Scholar 

  33. Ukkonen, E.: Approximate matching over suffix trees. LNCS, vol. 684, pp. 228–242. Springer, Heidelberg (1993)

    Google Scholar 

  34. Xia, B.B.: Similarity search in time series data sets. Technical report, School of Computer Science, Simon Fraser University (1997)

    Google Scholar 

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Authors and Affiliations

  1. Dipartimento di Informatica, Università del Piemonte Orientale, Alessandria, Italy

    Stefania Montani & Luigi Portinale

Authors
  1. Stefania Montani
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  2. Luigi Portinale
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Editors and Affiliations

  1. Department of Computer Science & Engineering, Lehigh University, PA 18015, Bethlehem,  

    Héctor Muñoz-Ávila

  2. Free University of Bozen-Bolzano,  

    Francesco Ricci

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Montani, S., Portinale, L. (2005). Case Based Representation and Retrieval with Time Dependent Features. In: Muñoz-Ávila, H., Ricci, F. (eds) Case-Based Reasoning Research and Development. ICCBR 2005. Lecture Notes in Computer Science(), vol 3620. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11536406_28

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  • DOI: https://doi.org/10.1007/11536406_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28174-0

  • Online ISBN: 978-3-540-31855-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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