Advertisement

Incremental Three-Way Decisions with Incomplete Information

  • Chuan Luo
  • Tianrui Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8536)

Abstract

The theory of rough sets proposed a framework for approximating concepts by three pair-wise disjoint regions, namely, the positive, boundary and negative regions. Rules generated by the three regions form three-way decision rules, which are acceptance, deferment and rejection decisions. The periodic updating of decision rules is required due to the dynamic nature of decision systems. Incremental learning technique is an effective way to solve the problem of dynamic data, which is capable of updating the learning results incrementally without recalculation in the total data set from scratch. In this paper, we present a methodology for incremental updating three-way decisions with incomplete information when the object set varies through the time.

Keywords

three-way decisions incremental updating incomplete decision system 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Altiparmak, F., Tuncel, E., Ferhatosmanoglu, H.: Incremental maintenance of online summaries over multiple streams. IEEE Transactions on Knowlege and Data Engineering 20(2), 216–229 (2008)CrossRefGoogle Scholar
  2. 2.
    Chen, H.M., Li, T.R., Ruan, D., Lin, J.H., Hu, C.X.: A rough-set based incremental approach for updating approximations under dynamic maintenance environments. IEEE Transactions on Knowledge and Data Engineering 25(2), 274–284 (2013)CrossRefGoogle Scholar
  3. 3.
    Fan, Y.N., Tseng, T.L., Chern, C.C., Huang, C.C.: Rule induction based on an incremental rough set. Expert Systems with Applications 36(9), 11439–11450 (2009)CrossRefGoogle Scholar
  4. 4.
    Luo, C., Li, T.R., Chen, H.M.: Dynamic maintenance of approximations in set-valued ordered decision systems under the attribute generalization. Information Sciences 257, 210–228 (2014)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Luo, C., Li, T.R., Chen, H.M., Liu, D.: Incremental approaches for updating approximations in set-valued ordered information systems. Knowledge-Based Systems 50, 218–233 (2013)CrossRefGoogle Scholar
  6. 6.
    Liu, D., Li, T., Liang, D.: Three-way decisions in dynamic decision-theoretic rough sets. In: Lingras, P., Wolski, M., Cornelis, C., Mitra, S., Wasilewski, P. (eds.) RSKT 2013. LNCS, vol. 8171, pp. 291–301. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  7. 7.
    Li, H., Zhou, X., Huang, B., Liu, D.: Cost-sensitive three-way decision: A sequential strategy. In: Lingras, P., Wolski, M., Cornelis, C., Mitra, S., Wasilewski, P. (eds.) RSKT 2013. LNCS, vol. 8171, pp. 325–337. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  8. 8.
    Liang, J., Wang, F., Dang, C., Qian, Y.: A group incremental approach to feature selection applying rough set technique. IEEE Transactions on Knowledge and Data Engineering 26(2), 294–308 (2012)CrossRefGoogle Scholar
  9. 9.
    Li, T.R., Ruan, D., Geert, W., Song, J., Xu, Y.: A rough sets based characteristic relation approach for dynamic attribute generalization in data ming. Knowledge-Based Systems 20, 485–494 (2007)CrossRefGoogle Scholar
  10. 10.
    Yao, Y.Y.: Probabilistic rough set approximations. International Journal of Approximation Reasoning 49, 255–271 (2008)CrossRefMATHGoogle Scholar
  11. 11.
    Yao, Y.Y.: Three-way decisions with probabilistic rough sets. Information Sciences 180, 341–353 (2010)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Yao, Y.Y.: The superiority of three-way decision in probabilistic rough set models. Information Sciences 181, 1080–1096 (2011)MathSciNetCrossRefMATHGoogle Scholar
  13. 13.
    Yao, Y.: Granular computing and sequential three-way decisions. In: Lingras, P., Wolski, M., Cornelis, C., Mitra, S., Wasilewski, P. (eds.) RSKT 2013. LNCS, vol. 8171, pp. 16–27. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  14. 14.
    Yao, Y.Y., Wong, S.K.M.: A decision-theoretic framework for approximating concepts. International Journal of Man-Machine Studies 37(6), 793–809 (1992)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Chuan Luo
    • 1
    • 2
  • Tianrui Li
    • 1
  1. 1.School of Information Science and TechnologySouthwest Jiaotong UniversityChengduChina
  2. 2.Department of Computer ScienceUniversity of ReginaReginaCanada

Personalised recommendations