Abstract
An action is defined as controlling or changing some of attribute values in an information system to achieve desired result. An action reduct is a minimal set of attribute values distinguishing a favorable object from other objects. We use action reducts to formulate necessary actions. The action suggested by an action reduct induces changes of decision attribute values by changing the condition attribute values to the distinct patterns in action reducts.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Gimpel, J.F.: A Reduction Technique for Prime Implicant Tables. In: The Fifth Annual Symposium on Switching Circuit Theory and Logical Design, pp. 183–191. IEEE, Washington (1964)
Pawlak, Z.: Rough Sets-Theoretical Aspects of Reasoning about Data. Kluwer, Dordrecht (1991)
Raś, Z.W., Wieczorkowska, A.A.: Action-Rules: How to Increase Profit of a Company. In: Zighed, D.A., Komorowski, J., Żytkow, J.M. (eds.) PKDD 2000. LNCS (LNAI), vol. 1910, pp. 587–592. Springer, Heidelberg (2000)
Geffner, H., Wainer, J.: Modeling Action, Knowledge and Control. ECAI, 532–536 (1998)
Greco, S., Matarazzo, B., Pappalardo, N., Slowinski, R.: Measuring Expected Effects of Interventions based on Decision Rules. Journal of Experimental and Theoretical Artificial Intelligence 17(1-2), 103–118 (2005)
Grzymala-Busse, J.: A New Version of the Rule Induction System LERS. Fundamenta Informaticae 31(1), 27–39 (1997)
He, Z., Xu, X., Deng, S., Ma, R.: Mining Action Rules from Scratch. Expert Systems with Applications 29(3), 691–699 (2005)
Hettich, S., Blake, C.L., Merz, C.J. (eds.): UCI Repository of Machine Learning Databases. University of California, Dept. of Information and Computer Sciences, Irvine (1998), http://www.ics.uci.edu/mlearn/MLRepository.html
Skowron, A.: Rough Sets and Boolean Reasoning. In: Pedrycz, W. (ed.) Granular Computing: An Emerging Paradigm, pp. 95–124. Springer, Heidelberg (2001)
Im, S., Ras, Z.W., Wasyluk, H.: Action Rule Discovery from Incomplete Data. Knowledge and Information Systems 25(1), 21–33 (2010)
Qiao, Y., Zhong, K., Wangand, H., Li, X.: Developing Event-Condition-Action Rules in Real-time Active Database. In: ACM Symposium on Applied Computing 2007, pp. 511–516. ACM, New York (2007)
Raś, Z.W., Dardzińska, A.: Action Rules Discovery, a New Simplified Strategy. In: Esposito, F., Raś, Z.W., Malerba, D., Semeraro, G. (eds.) ISMIS 2006. LNCS (LNAI), vol. 4203, pp. 445–453. Springer, Heidelberg (2006)
Ras, Z.W., Tzacheva, A., Tsay, L., Gurdal, O.: Mining for Interesting Action Rules. In: IEEE/WIC/ACM International Conference on Intelligent Agent Technology, pp. 187–193. IEEE, Washington (2005)
Raś, Z.W., Dardzińska, A.: Action Rules Discovery Based on Tree Classifiers and Meta-actions. In: Rauch, J., Raś, Z.W., Berka, P., Elomaa, T. (eds.) ISMIS 2009. LNCS(LNAI), vol. 5722, pp. 66–75. Springer, Heidelberg (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Im, S., Ras, Z., Tsay, LS. (2011). Action Reducts. In: Kryszkiewicz, M., Rybinski, H., Skowron, A., Raś, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2011. Lecture Notes in Computer Science(), vol 6804. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21916-0_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-21916-0_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21915-3
Online ISBN: 978-3-642-21916-0
eBook Packages: Computer ScienceComputer Science (R0)