46 research outputs found
Incremental complexity of a bi-objective hypergraph transversal problem
The hypergraph transversal problem has been intensively studied, from both a
theoretical and a practical point of view. In particular , its incremental
complexity is known to be quasi-polynomial in general and polynomial for
bounded hypergraphs. Recent applications in computational biology however
require to solve a generalization of this problem, that we call bi-objective
transversal problem. The instance is in this case composed of a pair of
hypergraphs (A, B), and the aim is to find minimal sets which hit all the
hyperedges of A while intersecting a minimal set of hyperedges of B. In this
paper, we formalize this problem, link it to a problem on monotone boolean
-- formulae of depth 3 and study its incremental complexity
Polynomial Delay Algorithm for Listing Minimal Edge Dominating sets in Graphs
The Transversal problem, i.e, the enumeration of all the minimal transversals
of a hypergraph in output-polynomial time, i.e, in time polynomial in its size
and the cumulated size of all its minimal transversals, is a fifty years old
open problem, and up to now there are few examples of hypergraph classes where
the problem is solved. A minimal dominating set in a graph is a subset of its
vertex set that has a non empty intersection with the closed neighborhood of
every vertex. It is proved in [M. M. Kant\'e, V. Limouzy, A. Mary, L. Nourine,
On the Enumeration of Minimal Dominating Sets and Related Notions, In Revision
2014] that the enumeration of minimal dominating sets in graphs and the
enumeration of minimal transversals in hypergraphs are two equivalent problems.
Hoping this equivalence can help to get new insights in the Transversal
problem, it is natural to look inside graph classes. It is proved independently
and with different techniques in [Golovach et al. - ICALP 2013] and [Kant\'e et
al. - ISAAC 2012] that minimal edge dominating sets in graphs (i.e, minimal
dominating sets in line graphs) can be enumerated in incremental
output-polynomial time. We provide the first polynomial delay and polynomial
space algorithm that lists all the minimal edge dominating sets in graphs,
answering an open problem of [Golovach et al. - ICALP 2013]. Besides the
result, we hope the used techniques that are a mix of a modification of the
well-known Berge's algorithm and a strong use of the structure of line graphs,
are of great interest and could be used to get new output-polynomial time
algorithms.Comment: proofs simplified from previous version, 12 pages, 2 figure
The Bases of Association Rules of High Confidence
We develop a new approach for distributed computing of the association rules
of high confidence in a binary table. It is derived from the D-basis algorithm
in K. Adaricheva and J.B. Nation (TCS 2017), which is performed on multiple
sub-tables of a table given by removing several rows at a time. The set of
rules is then aggregated using the same approach as the D-basis is retrieved
from a larger set of implications. This allows to obtain a basis of association
rules of high confidence, which can be used for ranking all attributes of the
table with respect to a given fixed attribute using the relevance parameter
introduced in K. Adaricheva et al. (Proceedings of ICFCA-2015). This paper
focuses on the technical implementation of the new algorithm. Some testing
results are performed on transaction data and medical data.Comment: Presented at DTMN, Sydney, Australia, July 28, 201
Computing knock out strategies in metabolic networks
Given a metabolic network in terms of its metabolites and reactions, our goal
is to efficiently compute the minimal knock out sets of reactions required to
block a given behaviour. We describe an algorithm which improves the
computation of these knock out sets when the elementary modes (minimal
functional subsystems) of the network are given. We also describe an algorithm
which computes both the knock out sets and the elementary modes containing the
blocked reactions directly from the description of the network and whose
worst-case computational complexity is better than the algorithms currently in
use for these problems. Computational results are included.Comment: 12 page
Enumerating all minimal hitting sets in polynomial total time
Consider a hypergraph (=set system) whose hyperedges are
subsets of a set with w elements. We show that the minimal hitting sets of
can be enumerated in polynomial total time .Comment: 8 page
Discovery of the D-basis in binary tables based on hypergraph dualization
Discovery of (strong) association rules, or implications, is an important
task in data management, and it nds application in arti cial intelligence,
data mining and the semantic web. We introduce a novel approach
for the discovery of a speci c set of implications, called the D-basis, that provides
a representation for a reduced binary table, based on the structure of
its Galois lattice. At the core of the method are the D-relation de ned in
the lattice theory framework, and the hypergraph dualization algorithm that
allows us to e ectively produce the set of transversals for a given Sperner hypergraph.
The latter algorithm, rst developed by specialists from Rutgers
Center for Operations Research, has already found numerous applications in
solving optimization problems in data base theory, arti cial intelligence and
game theory. One application of the method is for analysis of gene expression
data related to a particular phenotypic variable, and some initial testing is
done for the data provided by the University of Hawaii Cancer Cente
Discovery of the D-basis in binary tables based on hypergraph dualization
Discovery of (strong) association rules, or implications, is an important
task in data management, and it nds application in arti cial intelligence,
data mining and the semantic web. We introduce a novel approach
for the discovery of a speci c set of implications, called the D-basis, that provides
a representation for a reduced binary table, based on the structure of
its Galois lattice. At the core of the method are the D-relation de ned in
the lattice theory framework, and the hypergraph dualization algorithm that
allows us to e ectively produce the set of transversals for a given Sperner hypergraph.
The latter algorithm, rst developed by specialists from Rutgers
Center for Operations Research, has already found numerous applications in
solving optimization problems in data base theory, arti cial intelligence and
game theory. One application of the method is for analysis of gene expression
data related to a particular phenotypic variable, and some initial testing is
done for the data provided by the University of Hawaii Cancer Cente