On multi-adjoint concept lattices based on heterogeneous conjunctors

uncategorised

Authors

Jesús Medina

Manuel Ojeda-Aciego

Published

1 January 2012

Publication details

Fuzzy Sets Syst. vol. 208 , pages 95–110.

Links

Abstract

Citation

Please, cite this work as:

[MO12] J. Medina and M. Ojeda-Aciego. “On multi-adjoint concept lattices based on heterogeneous conjunctors”. In: Fuzzy Sets Syst. 208 (2012), pp. 95-110. DOI: 10.1016/J.FSS.2012.02.008. URL: https://doi.org/10.1016/j.fss.2012.02.008.

BibTeX

@Article{Medina2012,
     author = {Jes{’u}s Medina and Manuel Ojeda-Aciego},
     journal = {Fuzzy Sets Syst.},
     title = {On multi-adjoint concept lattices based on heterogeneous conjunctors},
     year = {2012},
     pages = {95–110},
     volume = {208},
     bibsource = {dblp computer science bibliography, https://dblp.org},
     biburl = {https://dblp.org/rec/journals/fss/MedinaO12.bib},
     doi = {10.1016/J.FSS.2012.02.008},
     timestamp = {Thu, 07 Jan 2021 00:00:00 +0100},
     url = {https://doi.org/10.1016/j.fss.2012.02.008},
}

Bibliometric data

The following data has been extracted from resources such as OpenAlex, Dimensions, PlumX or Altmetric.

Citations
CrossRef - Citation Indexes: 40
Scopus - Citation Indexes: 54

Captures
Mendeley - Readers: 10

Cites

The following graph plots the number of cites received by this work from its publication, on a yearly basis.

Papers citing this work

The following is a non-exhaustive list of papers that cite this work:

[1] Ľ. Antoni, P. Eliaš, J. Guniš, et al. “Bimorphisms and attribute implications in heterogeneous formal contexts”. In: International Journal of Approximate Reasoning 172 (Sep. 2024), p. 109245. ISSN: 0888-613X. DOI: 10.1016/j.ijar.2024.109245. URL: http://dx.doi.org/10.1016/j.ijar.2024.109245.

[2] L. Antoni, S. Krajči, and O. Krídlo. “Constraint heterogeneous concept lattices and concept lattices with heterogeneous hedges”. In: Fuzzy Sets and Systems 303 (Nov. 2016), p. 21–37. ISSN: 0165-0114. DOI: 10.1016/j.fss.2015.12.007. URL: http://dx.doi.org/10.1016/j.fss.2015.12.007.

[3] L. Antoni, S. Krajči, and O. Krídlo. “On stability of fuzzy formal concepts over randomized one-sided formal context”. In: Fuzzy Sets and Systems 333 (Feb. 2018), p. 36–53. ISSN: 0165-0114. DOI: 10.1016/j.fss.2017.04.006. URL: http://dx.doi.org/10.1016/j.fss.2017.04.006.

[4] L. Antoni, S. Krajči, and O. Krídlo. “Representation of fuzzy subsets by Galois connections”. In: Fuzzy Sets and Systems 326 (Nov. 2017), p. 52–68. ISSN: 0165-0114. DOI: 10.1016/j.fss.2017.05.020. URL: http://dx.doi.org/10.1016/j.fss.2017.05.020.

[5] L. Antoni, S. Krajči, O. Krídlo, et al. “On heterogeneous formal contexts”. In: Fuzzy Sets and Systems 234 (Jan. 2014), p. 22–33. ISSN: 0165-0114. DOI: 10.1016/j.fss.2013.04.008. URL: http://dx.doi.org/10.1016/j.fss.2013.04.008.

[6] P. Butka, J. Pócs, and J. Pócsová. “On equivalence of conceptual scaling and generalized one-sided concept lattices”. In: Information Sciences 259 (Feb. 2014), p. 57–70. ISSN: 0020-0255. DOI: 10.1016/j.ins.2013.08.047. URL: http://dx.doi.org/10.1016/j.ins.2013.08.047.

[7] M. E. Cornejo, J. Medina-Moreno, and E. Ramírez. “On the Classification of Fuzzy-Attributes in Multi-adjoint Concept Lattices”. In: Advances in Computational Intelligence. Springer Berlin Heidelberg, 2013, p. 266–277. ISBN: 9783642386824. DOI: 10.1007/978-3-642-38682-4_30. URL: http://dx.doi.org/10.1007/978-3-642-38682-4_30.

[8] M. E. Cornejo, J. Medina, and E. Ramírez-Poussa. “Adjoint negations, more than residuated negations”. In: Information Sciences 345 (Jun. 2016), p. 355–371. ISSN: 0020-0255. DOI: 10.1016/j.ins.2016.01.038. URL: http://dx.doi.org/10.1016/j.ins.2016.01.038.

[9] J. Díaz-Moreno, J. Medina, and M. Ojeda-Aciego. “On basic conditions to generate multi-adjoint concept lattices via Galois connections”. In: International Journal of General Systems 43.2 (Jan. 2014), p. 149–161. ISSN: 1563-5104. DOI: 10.1080/03081079.2013.879302. URL: http://dx.doi.org/10.1080/03081079.2013.879302.

[10] D. Dubois and H. Prade. “Bridging gaps between several forms of granular computing”. In: Granular Computing 1.2 (Jan. 2016), p. 115–126. ISSN: 2364-4974. DOI: 10.1007/s41066-015-0008-8. URL: http://dx.doi.org/10.1007/s41066-015-0008-8.

[11] F. García-Pardo, I. P. Cabrera, P. Cordero, et al. “On Galois Connections and Soft Computing”. In: Advances in Computational Intelligence. Springer Berlin Heidelberg, 2013, p. 224–235. ISBN: 9783642386824. DOI: 10.1007/978-3-642-38682-4_26. URL: http://dx.doi.org/10.1007/978-3-642-38682-4_26.

[12] R. Halaš and J. Pócs. “Generalized one-sided concept lattices with attribute preferences”. In: Information Sciences 303 (May. 2015), p. 50–60. ISSN: 0020-0255. DOI: 10.1016/j.ins.2015.01.009. URL: http://dx.doi.org/10.1016/j.ins.2015.01.009.

[13] J. Konecny, J. Medina, and M. Ojeda-Aciego. “Multi-adjoint concept lattices with heterogeneous conjunctors and hedges”. In: Annals of Mathematics and Artificial Intelligence 72.1–2 (Mar. 2014), p. 73–89. ISSN: 1573-7470. DOI: 10.1007/s10472-014-9405-y. URL: http://dx.doi.org/10.1007/s10472-014-9405-y.

[14] O. Krídlo, S. Krajči, and L. Antoni. “Formal concept analysis of higher order”. In: International Journal of General Systems 45.2 (Jan. 2016), p. 116–134. ISSN: 1563-5104. DOI: 10.1080/03081079.2015.1072924. URL: http://dx.doi.org/10.1080/03081079.2015.1072924.

[15] O. Krídlo and M. Ojeda-Aciego. “Revising the link between L-Chu correspondences and completely lattice L-ordered sets”. In: Annals of Mathematics and Artificial Intelligence 72.1–2 (Apr. 2014), p. 91–113. ISSN: 1573-7470. DOI: 10.1007/s10472-014-9416-8. URL: http://dx.doi.org/10.1007/s10472-014-9416-8.

[16] P. K. Singh. “Concept lattice visualization of data with m-polar fuzzy attribute”. In: Granular Computing 3.2 (Nov. 2017), p. 123–137. ISSN: 2364-4974. DOI: 10.1007/s41066-017-0060-7. URL: http://dx.doi.org/10.1007/s41066-017-0060-7.

[17] P. K. Singh. “m -polar fuzzy graph representation of concept lattice”. In: Engineering Applications of Artificial Intelligence 67 (Jan. 2018), p. 52–62. ISSN: 0952-1976. DOI: 10.1016/j.engappai.2017.09.011. URL: http://dx.doi.org/10.1016/j.engappai.2017.09.011.

[18] P. K. Singh. “Object and attribute oriented m-polar fuzzy concept lattice using the projection operator”. In: Granular Computing 4.3 (Jul. 2018), p. 545–558. ISSN: 2364-4974. DOI: 10.1007/s41066-018-0117-2. URL: http://dx.doi.org/10.1007/s41066-018-0117-2.

[19] P. K. Singh and C. Aswani Kumar. “Bipolar fuzzy graph representation of concept lattice”. In: Information Sciences 288 (Dec. 2014), p. 437–448. ISSN: 0020-0255. DOI: 10.1016/j.ins.2014.07.038. URL: http://dx.doi.org/10.1016/j.ins.2014.07.038.

[20] P. K. Singh, C. Aswani Kumar, and A. Gani. “A comprehensive survey on formal concept analysis, its research trends and applications”. In: International Journal of Applied Mathematics and Computer Science 26.2 (Jun. 2016), p. 495–516. ISSN: 2083-8492. DOI: 10.1515/amcs-2016-0035. URL: http://dx.doi.org/10.1515/amcs-2016-0035.

[21] P. K. Singh, C. Aswani Kumar, and J. Li. “Knowledge representation using interval-valued fuzzy formal concept lattice”. In: Soft Computing 20.4 (Feb. 2015), p. 1485–1502. ISSN: 1433-7479. DOI: 10.1007/s00500-015-1600-1. URL: http://dx.doi.org/10.1007/s00500-015-1600-1.

[22] P. K. Singh and A. K. Ch. “A Note on Constructing Fuzzy Homomorphism Map for a Given Fuzzy Formal Context”. In: Proceedings of the Third International Conference on Soft Computing for Problem Solving. Springer India, 2014, p. 845–855. ISBN: 9788132217718. DOI: 10.1007/978-81-322-1771-8_73. URL: http://dx.doi.org/10.1007/978-81-322-1771-8_73.

[23] P. K. Singh and C. A. Kumar. “Interval-valued fuzzy graph representation of concept lattice”. In: 2012 12th International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, Nov. 2012, p. 604–609. DOI: 10.1109/isda.2012.6416606. URL: http://dx.doi.org/10.1109/isda.2012.6416606.

[24] V. Vychodil. “Parameterizing the Semantics of Fuzzy Attribute Implications by Systems of Isotone Galois Connections”. In: IEEE Transactions on Fuzzy Systems 24.3 (Jun. 2016), p. 645–660. ISSN: 1941-0034. DOI: 10.1109/tfuzz.2015.2470530. URL: http://dx.doi.org/10.1109/tfuzz.2015.2470530.