Negative Attributes and Implications in Formal Concept Analysis

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Authors

José Manuel Rodríguez-Jiménez

Pablo Cordero

Manuel Enciso

Ángel Mora

Published

1 January 2014

Publication details

Proceedings of the Second International Conference on Information Technology and Quantitative Management, {ITQM} 2014, National Research University Higher School of Economics (HSE), Moscow, Russia, June 3-5, 2014 , Procedia Computer Science vol. 31, pages 758–765.

Links

Abstract

The mining of negative attributes from datasets has been studied in the last decade to obtain additional and useful information. There exists an exhaustive study around the notion of negative association rules between sets of attributes. However, in Formal Concept Analysis, the needed theory for the management of negative attributes is in an incipient stage. In this work we present an algorithm, based on the NextClosure algorithm, that allows to obtain mixed implications. The proposed algorithm returns a feasible and complete basis of mixed implications by performing a reduced number of requests to the formal context.

Citation

Please, cite this work as:

[Rod+14] J. M. Rodr'-Jiménez, P. Cordero, M. Enciso, et al. “Negative Attributes and Implications in Formal Concept Analysis”. In: Proceedings of the Second International Conference on Information Technology and Quantitative Management, ITQM 2014, National Research University Higher School of Economics (HSE), Moscow, Russia, June 3-5, 2014. Ed. by F. Aleskerov, Y. Shi and A. Lepskiy. Vol. 31. Procedia Computer Science. Elsevier, 2014, pp. 758-765. DOI: 10.1016/J.PROCS.2014.05.325. URL: https://doi.org/10.1016/j.procs.2014.05.325.

BibTeX

@InProceedings{RodriguezJimenez2014a,
     author = {Jos{’e} Manuel Rodr'-Jim{’e}nez and Pablo Cordero and Manuel Enciso and {’A}ngel Mora},
     booktitle = {Proceedings of the Second International Conference on Information Technology and Quantitative Management, {ITQM} 2014, National Research University Higher School of Economics (HSE), Moscow, Russia, June 3-5, 2014},
     title = {Negative Attributes and Implications in Formal Concept Analysis},
     year = {2014},
     editor = {Fuad Aleskerov and Yong Shi and Alexander Lepskiy},
     pages = {758–765},
     publisher = {Elsevier},
     series = {Procedia Computer Science},
     volume = {31},
     bibsource = {dblp computer science bibliography, https://dblp.org},
     biburl = {https://dblp.org/rec/conf/itqm/Rodriguez-JimenezCEM14.bib},
     doi = {10.1016/J.PROCS.2014.05.325},
     timestamp = {Tue, 20 Aug 2024 07:54:44 +0200},
     url = {https://doi.org/10.1016/j.procs.2014.05.325},
}

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Negative Attributes and Implications in Formal Concept Analysis

Cites

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Papers citing this work

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

[1] A. Bazin, M. Couceiro, M. Devignes, et al. “Steps towards causal Formal Concept Analysis”. In: International Journal of Approximate Reasoning 142 (Mar. 2022), p. 338–348. ISSN: 0888-613X. DOI: 10.1016/j.ijar.2021.12.007. URL: http://dx.doi.org/10.1016/j.ijar.2021.12.007.

[2] F. Chacón-Gómez, M. E. Cornejo, and J. Medina. “Towards Confirmation Measures to Mixed Attribute Implications”. In: Graph-Based Representation and Reasoning. Springer Nature Switzerland, 2023, p. 193–196. ISBN: 9783031409608. DOI: 10.1007/978-3-031-40960-8_16. URL: http://dx.doi.org/10.1007/978-3-031-40960-8_16.

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[22] H. Zhi and J. Li. “Granule description based knowledge discovery from incomplete formal contexts via necessary attribute analysis”. In: Information Sciences 485 (Jun. 2019), p. 347–361. ISSN: 0020-0255. DOI: 10.1016/j.ins.2019.02.032. URL: http://dx.doi.org/10.1016/j.ins.2019.02.032.

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