On homogeneous L-bonds and heterogeneous L-bonds

References

• Alcalde, C., A. Burusco, and R. Fuentes-González. 2010. “Interval-valued Linguistic Variables: An Application to the L-fuzzy Contexts with Absent Values.” International Journal of General Systems 39 (3): 255–270.
   Web of Science ®Google Scholar
• Alcalde, C., A. Burusco, and R. Fuentes-González. 2012. “Analysis of Certain L-Fuzzy Relational Equations and the Study of its solutions by Means of the L-Fuzzy Concept Theory.” International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 20 (1): 21–40.
   Web of Science ®Google Scholar
• Alcalde, C., A. Burusco, R. Fuentes-González, and I. Zubia. 2011. “The Use of Linguistic Variables and Fuzzy Propositions in the L-Fuzzy Concept Theory.” Computers & Mathematics with Applications 62 (8): 3111–3122.
   Web of Science ®Google Scholar
• Belohlavek, R. 1998. “Lattices Generated by Binary Fuzzy Relations (Extended Abstract).” In 4th International Conference on Fuzzy Sets Theory and Applications, 11. Liptovský Ján.
   Google Scholar
• Belohlavek, R. 1999. “Fuzzy Galois Connections.” Mathematical Logic Quarterly 45 (6): 497–504.
   Web of Science ®Google Scholar
• Belohlavek, R. 2001. “Fuzzy Closure Operators.” Journal of Mathematical Analysis and Applications 262 (2): 473–489.
   Web of Science ®Google Scholar
• Belohlavek, R. 2002. Fuzzy Relational Systems: Foundations and Principles. Norwell, MA: Kluwer Academic Publishers.
   Google Scholar
• Belohlavek, R. 2004. “Concept Lattices and Order in Fuzzy Logic.” Annals of Pure and Applied Logic 128 (1–3): 277–298.
   Web of Science ®Google Scholar
• Belohlavek, R., and J. Konecny. 2011. “Closure Spaces of Isotone Galois Connections and their Morphisms.” Lecture Notes in Computer Science 7106: 182–191.
   Google Scholar
• Belohlavek, R., and J. Konecny. 2012a. “Concept Lattices of Isotone vs. Antitone Galois Connections in Graded Setting: Mutual Reducibility Revisited.” Information Sciences 199: 133–137.
   Web of Science ®Google Scholar
• Belohlavek, R., and J. Konecny. 2012b. “Row and Column Spaces of Matrices over Residuated Lattices.” Fundamenta Informaticae 115 (4): 279–295.
   Web of Science ®Google Scholar
• Burusco, A., and R. Fuentes-González. 1994. “The Study of L-fuzzy Concept Lattice.” Mathware & Soft Computing 3: 209–218.
   Google Scholar
• Butka, P., J. Pócsová, and J. Pócs. 2012. “On Generation of One-sided Concept Lattices from Restricted Context.” In IEEE 10th Jubilee International Symposium on Intelligent Systems and Informatics (SISY), 111–115. Subotica.
   Google Scholar
• Chen, R. C., C. T. Bau, and C. J. Yeh. 2011. “Merging Domain Ontologies Based on the Wordnet System and Fuzzy Formal Concept Analysis Techniques.” Applied Soft Computing 11 (2): 1908–1923.
   Web of Science ®Google Scholar
• Díaz, J., and J. Medina. 2013. “Multi-adjoint Relation Equations: Definition, Properties and Solutions Using Concept Lattices.” Information Sciences 253: 100–109.
   Web of Science ®Google Scholar
• Díaz, J., J. Medina, and M. Ojeda-Aciego. 2014. “On Basic Conditions to Generate Multi-adjoint Concept Lattices via Galois Connections.” International Journal of General Systems 43 (2): 149–161.
   Web of Science ®Google Scholar
• Dubois, D., and H. Prade. 2012. “Possibility Theory and Formal Concept Analysis: Characterizing Independent Sub-contexts.” Fuzzy Sets and Systems 196: 4–16.
   Web of Science ®Google Scholar
• Falk, I., and C. Gardent. 2014. “Combining Formal Concept Analysis and Translation to Assign Frames and Semantic Role Sets to French Verbs.” Annals of Mathematics and Artificial Intelligence 70: 123–150.
   Web of Science ®Google Scholar
• Formica, A. 2012. “Semantic Web Search Based on Rough Sets and Fuzzy Formal Concept Analysis.” Knowledge-Based Systems 26: 40–47.
   Web of Science ®Google Scholar
• Ganter, B. 2007. “Relational Galois Connections.” Lecture Notes in Computer Science 4390: 1–17.
   Google Scholar
• Georgescu, G., and A. Popescu. 2004. “Non-dual Fuzzy Connections.” Archive for Mathematical Logic 43 (8): 1009–1039.
   Web of Science ®Google Scholar
• Goguen, J. 1967. “L-fuzzy Sets.” Journal of Mathematical Analysis and Applications 18: 145–174.
   Web of Science ®Google Scholar
• Kang, X., D. Li, S. Wang, and K. Qu. 2013. “Rough Set Model Based on Formal Concept Analysis.” Information Sciences 222: 611–625.
   Web of Science ®Google Scholar
• Kohout, L. J., and W. Bandler. 1985. “Relational-product Architectures for Information Processing.” Information Sciences 37 (1–3): 25–37.
   Web of Science ®Google Scholar
• Konecny, J. 2012. “Closure and Interior Structures in Relational Data Analysis and their Morphisms.” PhD thesis. Palacky University, Olomouc, Czech Republic.
   Google Scholar
• Kontopoulos, E., C. Berberidis, T. Dergiades, and N. Bassiliades. 2013. “Ontology-based Sentiment Analysis of Twitter Posts.” Expert systems with applications 40 (10): 4065–4074.
   Web of Science ®Google Scholar
• Krídlo, O., S. Krajči, and M. Ojeda-Aciego. 2012. “The Category of L-Chu Correspondences and the Structure of L-bonds.” Fundamenta Informaticae 115 (4): 297–325.
   Web of Science ®Google Scholar
• Krídlo, O., P. Mihalčin, S. Krajči, and L. Antoni. 2013. “Formal Concept Analysis of Higher Order.” In International Conference on Concept Lattices and their Applications, 117–128. La Rochelle, France.
   Google Scholar
• Krötzsch, M., P. Hitzler, and G.-Q. Zhang. 2005. “Morphisms in Context.” Lecture Notes in Computer Science 3596: 223–237.
   Google Scholar
• Lai, H., and D. Zhang. 2009. “Concept Lattices of Fuzzy Contexts: Formal Concept Analysis vs. Rough Set Theory.” International Journal of Approximate Reasoning 50 (5): 695–707.
   Web of Science ®Google Scholar
• Lei, Y., and M. Luo. 2009. “Rough Concept Lattices and Domains.” Annals of Pure and Applied Logic 159 (3): 333–340.
   Web of Science ®Google Scholar
• Li, S. T., and F. Tsai. 2011. “Noise Control in Document Classification Based on Fuzzy Formal Concept Analysis.” In FUZZ-IEEE’11, 2583–2588. La Rochelle, France.
   Google Scholar
• Medina, J. 2012. “Multi-adjoint Property-oriented and Object-oriented Concept Lattices.” Information Sciences 190: 95–106.
   Web of Science ®Google Scholar
• Medina, J., and M. Ojeda-Aciego. 2010. “Multi-adjoint t-concept Lattices.” Information Sciences 180 (5): 712–725.
   Web of Science ®Google Scholar
• Medina, J., and M. Ojeda-Aciego. 2012. “On Multi-adjoint Concept Lattices Based on Heterogeneous Conjunctors.” Fuzzy Sets and Systems 208: 95–110.
   Web of Science ®Google Scholar
• Medina, J., and M. Ojeda-Aciego. 2013. “Dual Multi-adjoint Concept Lattices.” Information Sciences 225: 47–54.
   Web of Science ®Google Scholar
• Medina, J., M. Ojeda-Aciego, and J. Ruiz-Calviño. 2009. “Formal Concept Analysis via Multi-adjoint Concept Lattices.” Fuzzy Sets and Systems 160 (2): 130–144.
   Web of Science ®Google Scholar
• Meschke, C. 2010. “Approximations in Concept Lattices.” Lecture Notes in Computer Science 5986: 104–123.
   Google Scholar
• Mora, A., et al. 2012. “Closure via Functional Dependence Simplification.” International Journal of Computer Mathematics 89 (4): 510–526.
   Web of Science ®Google Scholar
• Pollandt, S. 1997. Fuzzy Begriffe. Berlin: Springer.
   Google Scholar
• Valverde-Albacete, F. 2006. “Combining Soft and Hard Techniques for the Analysis of Batch Retrieval Tasks.” Studies in Fuzziness 197: 239–256.
   Google Scholar
• Valverde-Albacete, F., and C. Peláez-Moreno. 2006. “Extending Conceptualisation Modes for Generalised Formal Concept Analysis.” Information Sciences 181: 1888–1909.
   Web of Science ®Google Scholar
• Wu, Q., and Z. Liu. 2009. “Real Formal Concept Analysis Based on Grey-rough Set Theory.” Knowledge-Based Systems 22 (1): 38–45.
   Web of Science ®Google Scholar