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Automatic Extraction of Decision Rules from Non-deterministic Data Systems: Theoretical Foundations and SQL-Based Implementation

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Database Theory and Application (DTA 2009)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 64))

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Abstract

We present a framework for SQL-based extraction of decision rules from data, with no need of retrieving massive amounts of rows from a database. We also explain how to design efficient methods for mining non-deterministic data, without any intermediate stages related to the analysis of undetermined values.

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References

  1. Agrawal, R., Srikant, R.: Fast Algorithms for Mining Association Rules. In: Proc. of VLDB, pp. 487–499 (1994)

    Google Scholar 

  2. Ceglar, A., Roddick, J.F.: Association mining. ACM Comput. Surv. 38(2) (2006)

    Google Scholar 

  3. Çetintemel, U., Zdonik, S.B., Kossmann, D., Tatbul, N. (eds.) Proc. of SIGMOD (2009)

    Google Scholar 

  4. Chong, E.I., Das, S., Eadon, G., Srinivasan, J.: An efficient SQL-based RDF querying scheme. In: Proc. of VLDB, pp. 1216–1227 (2005)

    Google Scholar 

  5. Demri, S., Orłowska, E.: Incomplete Information: Structure, Inference, Complexity. Springer, Heidelberg (2002)

    MATH  Google Scholar 

  6. Grzymała-Busse, J.: Data with Missing Attribute Values: Generalization of Indiscernibility Relation and Rule Induction. Trans. Rough Sets 1, 78–95 (2004)

    Google Scholar 

  7. Infobright.org Forums, http://www.infobright.org/Forums/viewthread/288/ , http://www.infobright.org/Forums/viewthread/621/

  8. Kloesgen, W., Żytkow, J.M. (eds.): Handbook of Data Mining and Knowledge Discovery. Oxford University Press, Oxford (2002)

    MATH  Google Scholar 

  9. Kryszkiewicz, M.: Rules in Incomplete Information Systems. Information Sciences 113, 271–292 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  10. Lipski, W.: On Semantic Issues Connected with Incomplete Information Data Base. ACM Trans. DBS 4, 269–296 (1979)

    Google Scholar 

  11. Mitchell, T.: Machine Learning. Mc Graw Hill, Newyork (1998)

    Google Scholar 

  12. Nguyen, H.S., Nguyen, S.H.: Fast split selection method and its application in decision tree construction from large databases. Int. J. Hybrid Intell. Syst. 2(2), 149–160 (2005)

    MATH  Google Scholar 

  13. Pawlak, Z.: Information systems theoretical foundations. Inf. Syst. 6(3), 205–218 (1981)

    Article  MATH  MathSciNet  Google Scholar 

  14. Sakai, H., Hayashi, K., Nakata, M., Ślęzak, D.: The Lower System, the Upper System and Rules with Stability Factor in Non-deterministic Information Systems. In: Proc. of RSFDGrC (2009) (in print)

    Google Scholar 

  15. Sakai, H., Ishibashi, R., Nakata, M.: On Rules and Apriori Algorithm in Non-deterministic Information Systems. Trans. Rough Sets 9, 328–350 (2008)

    Google Scholar 

  16. Shafer, G.: A Mathematical Theory of Evidence. Princeton University Press, Princeton (1976)

    MATH  Google Scholar 

  17. Sarawagi, S., Thomas, S., Agrawal, R.: Integrating Association Rule Mining with Relational Database Systems: Alternatives and Implications. Research Report, http://www.almaden.ibm.com/cs/projects/iis/hdb/Publications/papers/sigmod98_dbi_rj.pdf

  18. Ślęzak, D., Eastwood, V.: Data warehouse technology by Infobright. In: Proc. of SIGMOD 2009, pp. 841–845 (2009)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Institute of Mathematics, University of Warsaw, Banacha 2, 02-097, Warsaw, Poland

    Dominik Ślęzak

  2. Infobright Inc., Poland, Krzywickiego 34 pok. 219, 02-078, Warsaw, Poland

    Dominik Ślęzak

  3. Department of Basic Sciences, Faculty of Engineering, Kyushu Institute of Technology Tobata, Kitakyushu 804, Japan

    Hiroshi Sakai

Authors
  1. Dominik Ślęzak
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  2. Hiroshi Sakai
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Editor information

Editors and Affiliations

  1. University of Warsaw and Infobright Inc., Poland

    Dominik Ślęzak

  2. Hannam University, 306-791, Daejeon, South Korea

    Tai-hoon Kim

  3. Utrecht University, The Netherlands

    Yanchun Zhang

  4. Hosei University, Tokyo, Japan

    Jianhua Ma

  5. ETRI, South Korea

    Kyo-il Chung

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© 2009 Springer-Verlag Berlin Heidelberg

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Ślęzak, D., Sakai, H. (2009). Automatic Extraction of Decision Rules from Non-deterministic Data Systems: Theoretical Foundations and SQL-Based Implementation. In: Ślęzak, D., Kim, Th., Zhang, Y., Ma, J., Chung, Ki. (eds) Database Theory and Application. DTA 2009. Communications in Computer and Information Science, vol 64. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10583-8_18

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  • DOI: https://doi.org/10.1007/978-3-642-10583-8_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10582-1

  • Online ISBN: 978-3-642-10583-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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