Εργαστήριο Γνώσης και Αβεβαιότητας

Knowledge and Uncertainty Research Laboratory

Computationally Efficient Incremental Transitive Closure of Sparse Fuzzy Binary Relations

[conference]


Full reference

M. Wallace, S. Kollias, Computationally Efficient Incremental Transitive Closure of Sparse Fuzzy Binary Relations, Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Budapest, Hungary, July 2004



6 known citations

  1. M. Falelakis, C. Diou and A. Delopoulos : Identification of Semantics: Balancing between Complexity and Validity, in Proc. IEEE Workshop on Multimedia Signal Processing (MMSP), Siena, Italy, October 2004.
  2. N. Mac Parthalain, R. Jensen, and Q. Shen. Finding Fuzzy-Rough Reducts with Fuzzy Entropy. Proceedings of the 2008 IEEE Conference on Fuzzy Systems, Hong Kong. 2008
  3. Falelakis, M., Diou, C., and Delopoulos, A. 2006. Semantic identification: balancing between complexity and validity. EURASIP J. Appl. Signal Process. 2006 (Jan. 2006), 183-183
  4. G. Moreno and V. Pascual. Programando con Igualdad Similar Estricta. In A. Fernandez, editor, Proc. of Campus Multidisciplinar en Percepcion e Inteligencia, CMPI-2006, Albacete, Spain, July 10-14, pages 712-724. Universidad de Castilla-La Mancha, 2006.
  5. Shu-Chen Wang. 2011. Hierarchical clustering in power system based on fuzzy transitive closure. WSEAS Trans. Cir. and Sys. 10, 10 (October 2011), 331-342.
  6. M. O. Incetaş, R. Demirci, H. G. Yavuzcan (2014). Automatic Segmentation of Color Images with Transitive Closure . AEU International Journal of Electronics and Communications, 68(270-276).