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Decision Rule Mining in Rough Set Theory

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Recommended Reading

  1. Gracia-Molina H, Ullman J, Windin J. Database systems the complete book. Upper Saddle Rive: Prentice Hall; 2002.

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  2. Lee TT. Algebraic theory of relational databases. Bell Syst Tech J. 1983;62(10):3159–204.

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  3. Lin TY. Rough set theory in very large databases. In: Proceedings of the Symposium in modelling analysis and Simulation. 1996. p. 936–41.

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  4. Lin TY. Granular computing on binary relations I: data mining and neighborhood systems. In: Skoworn A, Polkowski L, editors. Rough sets in knowledge discovery. Heidelberg/New York: Physica-Verlag; 1998. p. 107–21.

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  5. Lin TY. Granular computing on binary relations II: rough set representations and belief functions. In: Skoworn A, Polkowski L, editors. Rough sets in knowledge discovery. Heidelberg/New York: Physica-Verlag; 1998. p. 121–40.

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  6. Lin TY. Granular computing: fuzzy logic and rough sets. In: Zadeh L, Kacprzyk J, editors. Computing with words in information/intelligent systems. Heidelberg: Physica-Verlag; 1999. p. 183–200.

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  7. Lin TY. Granular computing: practices, theories, and future directions. Encyclopedia of complexity and systems science. 2009. p. 4339–55.

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  8. Lin TY, Han J. High frequent value reduct in very large databases. In: Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing; 2007. p. 346–54.

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  9. Lin TY, Liu Y, Huang W. Unifying rough set theories via large scaled granular computing. Fundam Inform. 2013;127(1–4):413–28.

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  10. Pawlak Z. Rough sets. Theoretical aspects of reasoning about data. Dordrecht: Kluwer Academic; 1991. ISBN:0-7923-1472-7.

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  11. Tsau-Young Lin: Np-hard problem in rough set theory, Bigdata 2017 (to appear)

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Lin, T.Y. (2018). Decision Rule Mining in Rough Set Theory. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_563

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