2,258 research outputs found
Clones in Graphs
Finding structural similarities in graph data, like social networks, is a
far-ranging task in data mining and knowledge discovery. A (conceptually)
simple reduction would be to compute the automorphism group of a graph.
However, this approach is ineffective in data mining since real world data does
not exhibit enough structural regularity. Here we step in with a novel approach
based on mappings that preserve the maximal cliques. For this we exploit the
well known correspondence between bipartite graphs and the data structure
formal context from Formal Concept Analysis. From there we utilize
the notion of clone items. The investigation of these is still an open problem
to which we add new insights with this work. Furthermore, we produce a
substantial experimental investigation of real world data. We conclude with
demonstrating the generalization of clone items to permutations.Comment: 11 pages, 2 figures, 1 tabl
Galois Connections between Semimodules and Applications in Data Mining
In [1] a generalisation of Formal Concept Analysis was introduced
with data mining applications in mind, K-Formal Concept Analysis,
where incidences take values in certain kinds of semirings, instead
of the standard Boolean carrier set. A fundamental result was missing
there, namely the second half of the equivalent of the main theorem of
Formal Concept Analysis. In this continuation we introduce the structural
lattice of such generalised contexts, providing a limited equivalent
to the main theorem of K-Formal Concept Analysis which allows to interpret
the standard version as a privileged case in yet another direction.
We motivate our results by providing instances of their use to analyse
the confusion matrices of multiple-input multiple-output classifiers
Characterizing One-Sided Formal Concept Analysis by Multi-Adjoint Concept Lattices
Managing and extracting information from databases is one of the main goals in several
fields, as in Formal Concept Analysis (FCA). One-sided concept lattices and multi-adjoint concept
lattices are two frameworks in FCA that have been developed in parallel. This paper shows that
one-sided concept lattices are particular cases of multi-adjoint concept lattices. As a first consequence
of this characterization, a new attribute reduction mechanism has been introduced in the one-side
framework.This research was partially supported by the 2014-2020 ERDF Operational Programme in collaboration with the State Research Agency (AEI) in Project 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
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