Clustering and identification of core implications

Clustering and identification of core implications

Authors

Domingo López-Rodríguez , Pablo Cordero , Manuel Enciso , Ángel Mora

Published

1 July 2021

Publication details

International Conference on Formal Concept Analysis (ICFCA) 2021

Links

DOI PDF

 

Abstract

FCA exhaustively uses the notion of cluster by grouping attributes and objects and providing a solid algebraic structure to them through the concept lattice. Our proposal explores how we can cluster implications. This work opens a research line to study the knowledge inside the clusters computed from the Duquenne-Guigues basis. Some alternative measures to induce the clusters are analysed, taking into account the information that directly appears in the appearance and the semantics of the implications. This work also allows us to show the fcaR package, which has the main methods of FCA and the Simplification Logic. The paper ends with a motivation of the potential applications of performing clustering on the implications.

Funding

NoteProjects funding this work

Citation

How to cite

D. López-Rodríguez, P. Cordero, M. Enciso, et al. “Clustering and Identification of Core Implications”. In: Formal Concept Analysis - 16th International Conference, ICFCA 2021, Strasbourg, France, June 29 - July 2, 2021, Proceedings. Ed. by A. Braud, A. Buzmakov, T. Hanika and F. L. Ber. Vol. 12733. Lecture Notes in Computer Science. Springer, 2021, pp. 138-154. DOI: 10.1007/978-3-030-77867-5_9. URL: https://doi.org/10.1007/978-3-030-77867-5_9.

BibTeX

<pre><code>

@inproceedings{Lopez-Rodriguez21, author = {Domingo López{-}Rodríguez and Pablo Cordero and Manuel Enciso and Angel Mora}, editor = {Agnès Braud and Aleksey Buzmakov and Tom Hanika and Florence Le Ber}, title = {Clustering and Identification of Core Implications}, booktitle = {Formal Concept Analysis - 16th International Conference, {ICFCA} 2021, Strasbourg, France, June 29 - July 2, 2021, Proceedings}, series = {Lecture Notes in Computer Science}, volume = {12733}, pages = {138–154}, publisher = {Springer}, year = {2021}, url = {https://doi.org/10.1007/978-3-030-77867-5_9}, doi = {10.1007/978-3-030-77867-5_9}, timestamp = {Tue, 13 Jul 2021 13:28:00 +0200}, biburl = {https://dblp.org/rec/conf/icfca/Lopez-Rodriguez21.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} }

<button class='copy-bib-btn' id='copy-bib-btn'><i class='bi bi-clipboard'></i> Copy BibTeX</button>

Bibliometric data

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

Clustering and identification of core implications

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. Uta Priss (2021). Modelling Conceptual Schemata with Formal Concept Analysis. FCA4AI@IJCAI
2. Unknown Author (n.d.). NA.
3. Unknown Author (n.d.). NA.
4. Unknown Author (n.d.). NA.
5. Unknown Author (n.d.). NA.
6. Unknown Author (n.d.). NA.