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Description Languages for Relational Information Granules

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Języki publikacji
EN
Abstrakty
EN
Information granulation is a powerful tool for data analysis and processing. However, not much attention has been devoted to application of this tool to data stored in a relational structure. This paper extends the notion of information granules to a relational case. Two information systems intended to store relational data are proposed. This study also extends a granule description language to express information granules derived from relational data. The proposed approach enables to analyze a given problem at different levels of granularity of relational data. This can find application in searching for patterns in data mining.
Wydawca
Rocznik
Strony
323--340
Opis fizyczny
Bibliogr. 15 poz., tab.
Twórcy
autor
  • Faculty of Computer Science Bialystok University of Technology Wiejska 45A, 15-351 Białystok, Poland
Bibliografia
  • [1] Bargiela, A., Pedrycz, W.: Granular Computing: An Introduction, Kluwer Academic Publishers, Boston, 2003.
  • [2] Bargiela, A., Pedrycz, W.: Toward a theory of granular computing for human-centered information processing, IEEE Transactions on Fuzzy Systems, 16(2), 2008, 320–330.
  • [3] Hońko, P.: Association discovery from relational data via granular computing, Information Sciences, 234, 2013, 136–149.
  • [4] Hońko, P.: Granular computing for relational data classification, Journal of Intelligent Information Systems, 41(2), 2013, 187–210.
  • [5] Lin, T. Y.: Introduction to special issues on data mining and granular computing, International Journal of Approximate Reasoning, 40(1–2), 2005, 1–2.
  • [6] Lin, T. Y.: Granular computing: Common practices and mathematical models, in: Proc. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2008), IEEE, 2008, 2405–2411.
  • [7] Lin, T. Y., Zadeh, L. A.: Special issue on granular computing and data mining, International Journal of Intelligent Systems, 19(7), 2004, 565–566.
  • [8] Pawlak, Z.: Rough Sets. Theoretical Aspects of Reasoning about Data, Kluwer Academic, Dordrecht, 1991.
  • [9] Pedrycz, W., Skowron, A., Kreinovich, V.: Handbook of Granular Computing, Wiley & Sons, New York, 2008.
  • [10] Skowron, A., Stepaniuk, J.: Information granules: Towards foundations of granular computing, International Journal of Intelligent Systems, 16(1), 2001, 57–85.
  • [11] Skowron, A., Stepaniuk, J.: Constrained sums of information systems, in: Rough Sets and Current Trends in Computing (S. Tsumoto, R. Slowinski, H. J. Komorowski, J.W. Grzymala-Busse, Eds.), vol. 3066 of Lecture Notes in Computer Science, Springer, 2004, 300–309.
  • [12] Skowron, A., Stepaniuk, J., Swiniarski, R.: Modeling rough granular computing based on approximation spaces, Information Sciences, 184(1), 2012, 20–43.
  • [13] Stepaniuk, J.: Rough-Granular Computing in Knowledge Discovery and Data Mining, Studies in Computational Intelligence 152, Springer-Verlag, Berlin-Heidelberg, 2008.
  • [14] Wróblewski, J.: Analyzing relational databases using rough set based methods, in: Proc. 8th Information Processing and Management of Uncertainty in Knowledge-Based Systems Conference (IPMU 2000), vol. 1, Consejo Superior de Investigaciones Cientifificas, Madrid, 2000, 256–262.
  • [15] Yao, Y. Y.: Granular computing: Basic issues and possible solutions, in: Proc. the 5th Joint Conference on Information Sciences (JCIS) (P. Wang, Ed.), Association for Intelligent Machinery, 2000, 186–189.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-48bb17d0-f6e0-44e6-861b-d462006aba03
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