Summary
In this paper we discuss tolerance information granule systems. We present examples of information granules and we consider two kinds of basic relations between them, namely inclusion and closeness. The relations between more complex information granules can be defined by extension of the relations defined on parts of information granules. In many application areas related to knowledge discovery in databases there is a need for algorithmic methods making it possible to discover relevant information granules. Examples of SQL implementations of discussed algorithms are included.
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
Dakowicz M., Stepaniuk J.: Tolerance Rough Sets and Data Base Management Systems, Proceedings of Concurrency, Specification and Programming Workshop, Czarna, Poland, September 25–27, 2003, 108–119.
Garcia-Molina H., Ullman J., Widom J.: Database Systems: The Complete Book, Prentice Hall, 2002.
Kloesgen W., Żytkow J. (Eds.): Handbook of Knowledge Discovery and Data Mining, Oxford University Press, Oxford, 2002.
Krawiec K., Slowinski R., Vanderpooten D.: Learning of Decision Rules from Similarity Based Rough Approximations. In: Skowron A., Polkowski L. (Eds.) Rough Sets in Knowledge Discovery. Physica Verlag, Heidelberg, 1998, 37–54.
Łukasiewicz J.: Die logischen grundlagen der wahrscheinilchkeitsrechnung, Krakow 1913. In Borkowski L., ed.: Jan Lukasiewicz-Selected Works. North Holland Publishing Company, Amstardam, London, Polish Scientific Publishers, Warsaw, 1970.
Pal S.K., Polkowski L., Skowron A. (Eds.): Rough-Neural Computing: Techniques for Computing with Words. Springer-Verlag, Berlin, 2004.
Pawlak Z.: Rough Sets. Theoretical Aspects of Reasoning about Data, Kluwer Academic Publishers, Dordrecht, 1991.
Skowron A., Stepaniuk J.: Generalized Approximation Spaces, Proceedings of the Third International Workshop on Rough Sets and Soft Computing, November 10–12, 1994, San Jose, California, USA, 18–21.
Skowron A., Stepaniuk J.: Tolerance Approximation Spaces, Fundamenta Informaticae, vol. 27(2,3), 1996, 245–253.
SQL standards: http://www.jcc.com/SQLPages/jccs_sql.htm.
Stepaniuk J.: Optimizations of Rough Set Model, Fundamenta Informaticae vol. 36(2–3), 1998, 265–283.
Stepaniuk J.: Knowledge Discovery by Application of Rough Set Models, L. Polkowski, S. Tsumoto, T.Y. Lin (Eds.), Rough Set Methods and Applications. New Developments in Knowledge Discovery in Information Systems, Physica-Verlag, Heidelberg, 2000, 137–233.
Zadeh L.A.: Toward a theory of fuzzy information granulation and its certainty in human reasoning and fuzzy logic. Fuzzy Sets and Systems 90, 1997, 111–127.
Zadeh L.A.: A new direction in AI: Toward a computational theory of perceptions. AI Magazine 22(1), 2001, 73–84.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Stepaniuk, J. (2005). Tolerance Information Granules. In: Monitoring, Security, and Rescue Techniques in Multiagent Systems. Advances in Soft Computing, vol 28. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32370-8_23
Download citation
DOI: https://doi.org/10.1007/3-540-32370-8_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23245-2
Online ISBN: 978-3-540-32370-9
eBook Packages: EngineeringEngineering (R0)