fcaR, Formal Concept Analysis with R

 

Abstract

Formal concept analysis (FCA) is a solid mathematical framework to manage information based on logic and lattice theory. It defines two explicit representations of the knowledge present in a dataset as concepts and implications. This paper describes an R package called fcaR that implements FCA’s core notions and techniques. Additionally, it implements the extension of FCA to fuzzy datasets and a simplification logic to develop automated reasoning tools. This package is the first to implement FCA techniques in R. Therefore, emphasis has been put on defining classes and methods that could be reusable and extensible by the community. Furthermore, the package incorporates an interface with the arules package, probably the most used package regarding association rules, closely related to FCA. Finally, we show an application of the use of the package to design a recommender system based on logic for diagnosis in neurological pathologies.

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Citation

Please, cite this work as:

[Cor+22] P. Cordero, M. Enciso, D. López-Rodríguez, et al. “fcaR, Formal Concept Analysis with R”. In: The R Journal 14 (1 2022). https://doi.org/10.32614/RJ-2022-014, pp. 341-361. ISSN: 2073-4859. DOI: 10.32614/RJ-2022-014.

BibTeX

@article{RJ-2022-014,
     author = {Pablo Cordero and Manuel Enciso and Domingo {López-Rodríguez} and Ángel Mora},
     title = {fcaR, Formal Concept Analysis with R},
     journal = {The R Journal},
     year = {2022},
     note = {https://doi.org/10.32614/RJ-2022-014},
     doi = {10.32614/RJ-2022-014},
     volume = {14},
     issue = {1},
     issn = {2073-4859},
     pages = {341-361}
}

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16

CITATIONS

16 Total citations

16 Recent citations

10 Field Citation Ratio

n/a Relative Citation Ratio

• Citations
• Scopus - Citation Indexes: 17

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• Mendeley - Readers: 11

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Cites

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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] N. Gondal and A. Wigen. “Professor-writers and machinist-painter-photographers: Investigating the duality between occupational categories and artistic hobbies”. In: Poetics 110 (Jun. 2025), p. 102001. ISSN: 0304-422X. DOI: 10.1016/j.poetic.2025.102001. URL: http://dx.doi.org/10.1016/j.poetic.2025.102001.

[3] J. Guniš, L. Šnajder, L. Antoni, et al. “Formal Concept Analysis of Students’ Solutions on Computational Thinking Game”. In: IEEE Transactions on Education 68.1 (Feb. 2025), p. 20–32. ISSN: 1557-9638. DOI: 10.1109/te.2024.3442612. URL: http://dx.doi.org/10.1109/te.2024.3442612.

[4] T. Hanika and R. Jäschke. “A Repository for Formal Contexts”. In: Conceptual Knowledge Structures. Springer Nature Switzerland, 2024, p. 182–197. ISBN: 9783031678684. DOI: 10.1007/978-3-031-67868-4_13. URL: http://dx.doi.org/10.1007/978-3-031-67868-4_13.

[5] O. Krídlo, D. López-Rodríguez, L. Antoni, et al. “Connecting concept lattices with bonds induced by external information”. In: Information Sciences 648 (Nov. 2023), p. 119498. ISSN: 0020-0255. DOI: 10.1016/j.ins.2023.119498. URL: http://dx.doi.org/10.1016/j.ins.2023.119498.

[6] D. López-Rodríguez and M. Ojeda-Hernández. “Rearrangement of Fuzzy Formal Contexts for Reducing Cost of Algorithms”. In: Conceptual Knowledge Structures. Springer Nature Switzerland, 2024, p. 113–122. ISBN: 9783031678684. DOI: 10.1007/978-3-031-67868-4_8. URL: http://dx.doi.org/10.1007/978-3-031-67868-4_8.

[7] D. López-Rodríguez, M. Ojeda-Hernández, and C. Bejines. “New Simplification Rules for Databases with Positive and Negative Attributes”. In: Mathematics 13.2 (Jan. 2025), p. 309. ISSN: 2227-7390. DOI: 10.3390/math13020309. URL: http://dx.doi.org/10.3390/math13020309.

[8] D. López-Rodríguez, M. Ojeda-Hernández, and T. Pattison. “Systems of implications obtained using the Carve decomposition of a formal context”. In: Knowledge-Based Systems (Apr. 2025), p. 113475. ISSN: 0950-7051. DOI: 10.1016/j.knosys.2025.113475. URL: http://dx.doi.org/10.1016/j.knosys.2025.113475.

[9] M. Ojeda-Hernández and D. López-Rodríguez. “Enhancing Performance of FCA Algorithms via Rearrangement of Formal Contexts”. In: 2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, Jun. 2024, p. 1–6. DOI: 10.1109/fuzz-ieee60900.2024.10612009. URL: http://dx.doi.org/10.1109/fuzz-ieee60900.2024.10612009.

[10] M. Ojeda-Hernández, D. López-Rodríguez, and Á. Mora. “A Formal Concept Analysis approach to hierarchical description of malware threats”. In: Forensic Science International: Digital Investigation 50 (Sep. 2024), p. 301797. ISSN: 2666-2817. DOI: 10.1016/j.fsidi.2024.301797. URL: http://dx.doi.org/10.1016/j.fsidi.2024.301797.

[11] M. Ojeda-Hernández, D. López-Rodríguez, and Á. Mora. “Lexicon-based sentiment analysis in texts using Formal Concept Analysis”. In: International Journal of Approximate Reasoning 155 (Apr. 2023), p. 104–112. ISSN: 0888-613X. DOI: 10.1016/j.ijar.2023.02.001. URL: http://dx.doi.org/10.1016/j.ijar.2023.02.001.

[12] C. Rungruang, P. Riyapan, A. Intarasit, et al. “RFM model customer segmentation based on hierarchical approach using FCA”. In: Expert Systems with Applications 237 (Mar. 2024), p. 121449. ISSN: 0957-4174. DOI: 10.1016/j.eswa.2023.121449. URL: http://dx.doi.org/10.1016/j.eswa.2023.121449.

[13] I. Sadriddinov, S. Peng, S. Siet, et al. “Algorithm for Mining Maximal Balanced Bicliques Using Formal Concept Analysis”. In: IEEE Access 13 (2025), p. 35113–35123. ISSN: 2169-3536. DOI: 10.1109/access.2024.3419838. URL: http://dx.doi.org/10.1109/access.2024.3419838.

[14] P. Sokol, Ľ. Antoni, O. Krídlo, et al. “Formal concept analysis approach to understand digital evidence relationships”. In: International Journal of Approximate Reasoning 159 (Aug. 2023), p. 108940. ISSN: 0888-613X. DOI: 10.1016/j.ijar.2023.108940. URL: http://dx.doi.org/10.1016/j.ijar.2023.108940.

[15] F. J. Valverde-Albacete and C. Peláez-Moreno. “A Formalization of Multilabel Classification in Terms of Lattice Theory and Information Theory: Concerning Datasets”. In: Mathematics 12.2 (Jan. 2024), p. 346. ISSN: 2227-7390. DOI: 10.3390/math12020346. URL: http://dx.doi.org/10.3390/math12020346.

[16] L. Yao, S. Wang, Q. Li, et al. “Continuous lattices in formal concept analysis”. In: Soft Computing 28.2 (Dec. 2023), p. 955–962. ISSN: 1433-7479. DOI: 10.1007/s00500-023-09462-5. URL: http://dx.doi.org/10.1007/s00500-023-09462-5.