=Paper=
{{Paper
|id=Vol-2378/shortAT4
|storemode=property
|title=FCA Tools Bundle
|pdfUrl=https://ceur-ws.org/Vol-2378/shortAT4.pdf
|volume=Vol-2378
|authors=Diana Cristea,Christian Săcărea, Diana-Florina Şotropa
|dblpUrl=https://dblp.org/rec/conf/icfca/CristeaSS19
}}
==FCA Tools Bundle==
https://ceur-ws.org/Vol-2378/shortAT4.pdf
FCA Tools Bundle
Diana Cristea, Christian Săcărea, and Diana-Florina Şotropa
Babeş-Bolyai University Cluj-Napoca
dianat@cs.ubbcluj.ro, csacarea@cs.ubbcluj.ro, diana.halita@ubbcluj.ro
Abstract. Formal Concept Analysis is well known for the intuitive and
graphical representations of lattices. While there are a lot of algorithms
mining for formal concepts in the dyadic case, there are not many tools
offering this feature for multidimensional datasets. The purpose of this
paper is to present FCA Tools Bundle and its various features, ranging
from importing the data in several formats to offering full support to
explore your data using different navigation and exploration methods.
1 Introduction
As an applied discipline, dealing with collections of knowledge, so-called con-
cepts, and aiming to detect, extract, process and represent patterns in various
data sets, FCA needs powerful software tools for handling not only the ”classical”
dyadic case - formal contexts and lattice representation, but also many-valued
contexts, conceptual scale building, triadic FCA, pattern structures, etc. While
the theory developed quickly, many software tools have been developed, but they
are rather specialized on one topic than to provide a collection of tools. In this
paper we present FCA Tools Bundle, a collection of tools covering not only the
dyadic case, but also handling many-valued contexts, supporting scale building
and conceptual browsing.
2 Related Work
While FCA focuses on data visualization and exploration, there are multiple al-
gorithms and software tools supporting it. An overview of this developing effort
is maintained by Uta Priss on her page 1 . Among them we briefly recall ToscanaJ
Suite [2], which is a Java implementation of the former tool Toscana and was
for many years the only tool to handle many-valued contexts. It includes tools to
create a formal context, perform conceptual scaling on a context, compute the
formal concepts and the corresponding concept lattice. Since all these features
are vital to FCA, they were also included in FCA Tools Bundle. Other impor-
tant algorithms and tools include: Trias [3], which is one of the few algorithms
Copyright c 2019 for this paper by its authors. Copying permitted for private and
academic purposes.
1
http://www.upriss.org.uk/fca/fcasoftware.html
2 Cristea et al.
that deals with triadic data or Lattice miner2 [8], a tool that implements gen-
eration and visualization of concept lattices. While most FCA tools focus on
basic features such as lattice visualization, and concept generation, some tools
try to integrate multiple features. For instance, LatViz [1] integrates functional-
ities such as visualization of Pattern Structures and implications, AOC posets,
concept annotations.
3 FCA Tools Bundle - Motivation and Features
While many of the FCA features are available in at least one software, the
problem lies in the fact that there does not exist a tool integrating all the features.
Also many of the tools, while being useful to FCA experts, are hard to use for non
experts. Therefore, making FCA more popular outside of its natural community
is another goal which motivates the development of FCA Tools Bundle3 .
A first version of the tool which was focused on navigation through the con-
cepts was presented earlier in more details [4]. However, since then new features
were added to the tool, such as: scale building and computing weak analogical
proportions. The FCA Tools Bundle currently implements features for dyadic
and triadic FCA, bridging the gap between the dyadic and the many-valued
case. Besides basic features, the tool includes some new approaches regarding
data exploration, such as constraint based navigation in n-adic datasets and the
visualization of weak analogical proportions in concept sets. Because the lack of
space we will enumerate the tools features, but we will only get into details for
some of the features that stand out. The list of features integrated in FCA Tools
Bundle includes the following:
1. Create dyadic or triadic contexts;
2. Import polyadic contexts and generate the correspondent concept set;
3. Build and view concept lattices;
4. Find a concept in a polyadic context without generating all its concepts;
5. Local navigation in triadic concept sets;
6. Import many-valued contexts and build conceptual scales;
7. Find Weak Analogical Proportions in concept sets;
To start exploring your own data the tool offers several methods of creating
the context: manually or by importing different formats. Conceptual scaling was
integrated in FCA Tools Bundle in a user friendly way as seen in Figure 1.
Currently the tool supports the nominal, ordinal, interordinal, grid or custom
scales. Moreover, the concept lattices generation was improved using a detection
collision algorithm, in order to avoid manually arranging the concept lattice for
concept visibility.
As mentioned previously, FCA Tools Bundle concentrates not only on dyadic,
but also on n-adic contexts. Therefore, the tool has integrated Trias [3] in order
2
https://sourceforge.net/projects/lattice-miner
3
https://fca-tools-bundle.com/
FCA Tools Bundle 3
Fig. 1: Generating a grid scale in FCA Tools Bundle
to generate a list of concepts in a triadic context. Based on the generated tri-
concepts the tool offers a navigation through a triadic context based on dyadic
projections. This navigation paradigm was described in more details and ana-
lyzed formally in previous papers [10, 4].
On the other hand, when dealing with n-adic datasets there are not many
algorithms computing formal concepts. Another important aspect that we took
into consideration is exploring a large dataset from the perspective of a user
that is looking for a cluster of elements having some particular properties. This
led us to the idea of a constraint based concept exploration in n-adic datasets
[9], which, to the best of our knowledge, is a feature that is not included in any
other tool. This was implemented using answer set programming (ASP), a logic
programming approach, and is an intuitive way to explore your data even for
non-technical users as it can be seen in Figure 2.
Another new feature of FCA Tools Bundle is displaying formal concepts in
weak analogical proportions. Analogical proportion ([5–7]) is a key pattern which
is associated with the idea of analogical reasoning and represents a statement
between two pairs (A, B) and (C, D) of the form A is to B as C is to D where
all elements A, B, C, D are in the same category. Analogical proportions can be
formulated for numbers, sets, in the boolean case, strings, as well as in various
algebraic structures, like semigroups or lattices. As explained in a previous paper
[11], if we denote by Ox and Ax the extent, respectively the intent of concept x,
then, by the main theorem of FCA, we have that four elements (x, y, z, t) of a
lattice are in a Weak Analogical Proportion (WAP) iff
Ax ∩ At = Ay ∩ Az and Ox ∩ Ot = Oy ∩ Oz .
When selecting a WAP from a list in FCA Tools Bundle the formal concepts
which are part of the WAP are highlighted as in Figure 3. This feature can be
4 Cristea et al.
Fig. 2: Constraint based concept exploration
Fig. 3: Visualizing analogical proportions in a concept lattice
very useful since it is interesting to find relations between concepts that are not
directly linked in a concept lattice. The computation is done by using an ASP
algorithm proposed by Miclet et. al [6].
FCA Tools Bundle 5
4 Conclusions and Future Work
In this paper we have presented the features integrated in FCA Tools Bundle, a
platform which aims to offer a comprehensive range of FCA features accessible
not only to FCA experts, but also to users outside the FCA community. We be-
lieve that FCA Tools Bundle is an important progress towards a self contained
FCA platform, by implementing functionalities such as visualization and navi-
gation in dyadic and n-adic datasets including some features which, to the best
of our knowledge, are not present in any other tool.
For the future we plan to integrate in the FCA Tools Bundle more features of
FCA that would allow an enhanced data analysis, such as computing implications
and pattern structures.
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