@misc{10498/30938,
year = {2022},
url = {http://hdl.handle.net/10498/30938},
abstract = {Formal concept analysis (FCA) is a useful mathematical tool for obtaining
information from relational datasets. One of the most interesting research
goals in FCA is the selection of the most representative variables of the
dataset, which is called attribute reduction. Recently, the attribute reduction
mechanism has been complemented with the use of local congruences
in order to obtain robust clusters of concepts, which form convex sublattices
of the original concept lattice. Since the application of such local congruences
modifies the quotient set associated with the attribute reduction, it
is fundamental to know how the original context (attributes, objects and
relationship) has been modified in order to understand the impact of the
application of the local congruence in the attribute reduction.},
organization = {Partially supported by the the 2014-2020 ERDF Operational Programme in collaboration
with the State Research Agency (AEI) in project TIN2016-76653-P and PID2019-
108991GB-I00, and with the Department of Economy, Knowledge, Business and University
of the Regional Government of Andalusia in project FEDER-UCA18-108612, and
by the European Cooperation in Science & Technology (COST) Action CA17124.},
publisher = {Elsevier},
keywords = {Formal concept analysis},
keywords = {size concept lattice reduction},
keywords = {congruence relation},
title = {Impact of local congruences in variable selection from datasets},
doi = {10.1016/j.cam.2021.113416},
author = {García Aragón, Roberto and Medina Moreno, Jesús and Ramírez Poussa, Eloísa},
}