USING CASE-BASED REASONING TO EXPLAIN EXCEPTIONAL CASES

Rainer Schmidt, Olga Vorobieva

2008

Abstract

In medicine many exceptions occur. In medical practice and in knowledge-based systems too, it is necessary to consider them and to deal with them appropriately. In medical studies and in research, exceptions shall be explained. We present a system that helps to explain cases that do not fit into a theoretical hypothesis. Our starting points are situations where neither a well-developed theory nor reliable knowledge nor a case base is available at the beginning. So, instead of reliable theoretical knowledge and intelligent experience, we have just some theoretical hypothesis and a set of measurements. In this paper, we propose to combine Case-Based Reasoning with a statistical model. We use Case-Based Reasoning to explain those cases that do not fit the model. The case base has to be set up incrementally, it contains the exceptional cases, and their explanations are the solutions, which can be used to help to explain further exceptional cases.

References

  1. Arshadi, N., Jurisica, I., 2005. Data Mining for Case-based Reasoning in high-dimensional biological domains. IEEE Transactions on Knowledge and Data Engineering 17 (8). 1127-1137
  2. Bichindaritz, I., Kansu, E., Sullivan, K.M., 1998. Casebased Reasoning in Care-Partner. In: EWCBR-98, European Workshop on Case-Based Reasoning. Springer, Berlin, 334-345
  3. Corchado, J.M., Corchado, E.S., Aiken, J., Fife, C., Fernandez, F., Gonzalez, M., 2003. Maximum likelihood Hebbian learning based retrieval method for CBR systems. In: ICCBR-2003, International Conference on Case-Based Reasoning. Springer, Berlin, 107-121
  4. Davidson, A.M., Cameron, J.S., Grünfeld, J.-P. (eds.), 2005. Oxford Textbook of Nephrology, Volume 3. Oxford University Press
  5. Hai, G.A., 2002. Logic of diagnostic and decision making in clinical medicine. Politheknica publishing, St. Petersburg
  6. Kendall, M.G., Stuart, A., 1979. The advanced theory of statistics. Macmillan publishing, New York
  7. Prentzas, J., Hatzilgeroudis, I., 2002. Integrating Hybrid Rule-Based with Case-Based Reasoning. In ECCBR2002, European Conference on Case-Based Reasoning. Springer, Berlin 336-349
  8. Rezvani, S., Prasad, G., 2003. A hybrid system with multivariate data validation and Case-based Reasoning for an efficient and realistic product formulation. In ICCBR-2003, International Conference on Case-Based Reasoning. Springer, Berlin (2003) 465-478
  9. Shuguang, L., Qing, J., George, C., 2000: Combining case-based and model-based reasoning: a formal specification. In APSEC'00, Asia Pacific Software Engineering Conference, 416
Download


Paper Citation


in Harvard Style

Schmidt R. and Vorobieva O. (2008). USING CASE-BASED REASONING TO EXPLAIN EXCEPTIONAL CASES . In Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-8111-37-1, pages 119-124. DOI: 10.5220/0001669501190124


in Bibtex Style

@conference{iceis08,
author={Rainer Schmidt and Olga Vorobieva},
title={USING CASE-BASED REASONING TO EXPLAIN EXCEPTIONAL CASES},
booktitle={Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2008},
pages={119-124},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001669501190124},
isbn={978-989-8111-37-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Tenth International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - USING CASE-BASED REASONING TO EXPLAIN EXCEPTIONAL CASES
SN - 978-989-8111-37-1
AU - Schmidt R.
AU - Vorobieva O.
PY - 2008
SP - 119
EP - 124
DO - 10.5220/0001669501190124