103 research outputs found
Towards a generalisation of formal concept analysis for data mining purposes
In this paper we justify the need for a generalisation of Formal
Concept Analysis for the purpose of data mining and begin the
synthesis of such theory. For that purpose, we first review semirings and
semimodules over semirings as the appropriate objects to use in abstracting
the Boolean algebra and the notion of extents and intents, respectively.
We later bring to bear powerful theorems developed in the field
of linear algebra over idempotent semimodules to try to build a Fundamental
Theorem for K-Formal Concept Analysis, where K is a type of
idempotent semiring. Finally, we try to put Formal Concept Analysis in
new perspective by considering it as a concrete instance of the theory
developed
Injecting Abstract Interpretations into Linear Cost Models
We present a semantics based framework for analysing the quantitative
behaviour of programs with regard to resource usage. We start from an
operational semantics equipped with costs. The dioid structure of the set of
costs allows for defining the quantitative semantics as a linear operator. We
then present an abstraction technique inspired from abstract interpretation in
order to effectively compute global cost information from the program.
Abstraction has to take two distinct notions of order into account: the order
on costs and the order on states. We show that our abstraction technique
provides a correct approximation of the concrete cost computations
Order automorphisms on the lattice of residuated maps of some special nondistributive lattices.
The residuated maps from a lattice L to itself form their own lattice, which we denote Res(L). In this dissertation, we explore the order automorphisms on the lattice Res(L) where L is a finite nondistributive lattice. It is known that left and right composition of f ∈ Res(L) with automorphisms of L yields an order automorphism of Res(L). It begs the question, then, if all order automorphisms of Res(L) can be classified as such
Parameterizing the semantics of fuzzy attribute implications by systems of isotone Galois connections
We study the semantics of fuzzy if-then rules called fuzzy attribute
implications parameterized by systems of isotone Galois connections. The rules
express dependencies between fuzzy attributes in object-attribute incidence
data. The proposed parameterizations are general and include as special cases
the parameterizations by linguistic hedges used in earlier approaches. We
formalize the general parameterizations, propose bivalent and graded notions of
semantic entailment of fuzzy attribute implications, show their
characterization in terms of least models and complete axiomatization, and
provide characterization of bases of fuzzy attribute implications derived from
data
A multi-modal logic for Galois connections
Advances in Modal Logic 2022
(Rennes, August 22-25
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