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## Desenvolvimento financeiro e restrição financeira nas decisões de investimento da firma: evidências para o Brasil; Financial development and financial constraint on firm's investment decisions: evidence for Brazil

Fonte: Biblioteca Digitais de Teses e Dissertações da USP
Publicador: Biblioteca Digitais de Teses e Dissertações da USP

Tipo: Dissertação de Mestrado
Formato: application/pdf

Publicado em 21/02/2011
PT

Relevância na Pesquisa

36.01%

#Decisões de investimento#Desenvolvimento financeiro#Financial constraint#Financial development#Investment decisions#Restrição financeira

Este trabalho tem como objetivo examinar os efeitos do desenvolvimento financeiro e das restrições financeiras nas decisões de investimento da firma considerando um conjunto de informações de 659 firmas brasileiras no período de 1998 a 2006. A investigação é realizada dentro de um contexto teórico e aplicado, considerando um modelo econométrico com dados longitudinais e assumindo que o desenvolvimento financeiro exerce impacto substancial nas restrições financeiras das firmas, o que está diretamente relacionado às suas decisões de investimento. Com o propósito de contribuir para a escassa literatura internacional e à inexistente literatura para o Brasil, este trabalho utilizou o índice KZ para classificação das firmas como financeiramente restritas e não restritas. Por meio do uso de dados macroeconômicos em uma análise microeconômica, empregou-se o modelo probabilístico logit para encontrar os principais fatores determinantes da probabilidade de restrição financeira das firmas brasileiras. Já para analisar a relação entre desenvolvimento financeiro, restrições financeiras e investimento da firma, estimou-se uma versão do modelo acelerador do investimento pelo método dos momentos generalizados (GMM) devido seu caráter dinâmico e à presença do problema de endogeneidade. Os principais resultados indicaram que...

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## Topic maps constraint specification languages : comparing AsTMa!, OSL, and XTche

Fonte: Universidade do Minho
Publicador: Universidade do Minho

Tipo: Conferência ou Objeto de Conferência

Publicado em 21/03/2007
ENG

Relevância na Pesquisa

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Topic maps are an ISO standard for the representation and interchange of knowledge, with an emphasis on the findability
of information. A topic map can represent information using topics (representing any concept), associations (which
represent the relationships between them), and occurrences (which represent relationships between topics and
information resources relevant to them). They are thus similar to semantic networks and both concept and mind maps in
many respects. According to Topic Map Data Model (TMDM), Topic Maps are abstract structures that can
encode knowledge and connect this encoded knowledge to relevant information resources.
In order to cope with a broad range of scenarios, a topic is a very wide concept. On one hand, this makes Topic Maps a
convenient model for knowledge representation; but on the other hand, this can also put in risk the topic map
consistency. A set of semantic constraints must be imposed to the topic map in order to grant its consistency.
Currently, we can find three approaches to constrain Topic Maps -- AsTMa!, OSL, and
XTche -- that allow us to specify constraints and to validate the instances of a family of
topic maps against that set of rules. With these resemblances it is easy to conclude that they are quite similar.
However they differ in some fundamental concepts. These three Topic Maps constraint specification languages were hardly
tested and benchmarked with a huge test suite. The most significant results will be discussed in this paper.
In this article...

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## Constraint-aware schema transformation

Fonte: Elsevier
Publicador: Elsevier

Tipo: Artigo de Revista Científica

Publicado em //2012
POR

Relevância na Pesquisa

35.95%

#Schema transformation#Invariants#Data refinement#Strategic term rewriting#Point-free program transformation#Haskell#Constraints

Ninth International Workshop on Rule-Based Programming (Rule 2008); Data schema transformations occur in the context of software evolution, refactoring, and cross-paradigm
data mappings. When constraints exist on the initial schema, these need to be transformed into constraints
on the target schema. Moreover, when high-level data types are refined to lower level structures, additional
target schema constraints must be introduced to balance the loss of structure and preserve semantics.
We introduce an algebraic approach to schema transformation that is constraint-aware in the sense that
constraints are preserved from source to target schemas and that new constraints are introduced where
needed. Our approach is based on refinement theory and point-free program transformation. Data refinements
are modeled as rewrite rules on types that carry point-free predicates as constraints. At each rewrite
step, the predicate on the reduct is computed from the predicate on the redex. An additional rewrite system
on point-free functions is used to normalize the predicates that are built up along rewrite chains.
We implemented our rewrite systems in a type-safe way in the functional programming language Haskell.
We demonstrate their application to constraint-aware hierarchical-relational mappings.

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## Algorithms to infer metabolic flux ratios from fluxomics data

Fonte: IEEE
Publicador: IEEE

Tipo: Conferência ou Objeto de Conferência

Publicado em /12/2013
ENG

Relevância na Pesquisa

35.96%

#Biochemistry#Biology computing#Cellular biophysics#Genomics#13C labeling distribution#Carbon atom transition maps#Constraint-based methods#Flux balance analysis#Fluxomics data#Genome-scale metabolic models#in silico cell simulation

In silico cell simulation approaches based in the use of genome-scale metabolic models (GSMMs) and constraint-based methods such as Flux Balance Analysis are gaining importance, but methods to integrate these approaches with omics data are still greatly needed. In this work, the focus relies on fluxomics data that provide valuable information on the intracellular fluxes, although in many cases in an indirect, incomplete and noisy way. The proposed framework enables the integration of fluxomics data, in the form of 13C labeling distribution for metabolite fragments, with GSMMs enriched with carbon atom transition maps. The algorithms implemented allow to infer labeling distributions for fragments/metabolites not measured and to build expressions for the relevant flux ratios that can be then used to enrich constraint-based methods for flux determination. This approach does not require any assumptions on the metabolic network and reaction reversibility, allowing to compute ratios originating from coupled joint points of the network. Also, when enough data do not exist, the system tries to infer ratio bounds from the measurements.

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## A Parallel and Distributed Framework for Constraint Solving

Fonte: Università degli Studi di Perugia
Publicador: Università degli Studi di Perugia

Tipo: Artigo de Revista Científica

ENG

Relevância na Pesquisa

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With the increased availability of affordable parallel and dis- tributed hardware, programming models for these architectures has be- come the focus of significant attention. Constraint programming, which can be seen as the encoding of processes as a Constraint Satisfaction Problem, because of its data-driven and control-insensitive approach is a prime candidate to serve as the basis for a framework which effectively exploits parallel architectures.
To effectually apply the power of distributed computational systems, there must be an effective sharing of the work involved in the search for a solution to a Constraint Satisfaction Problem (CSP) between all the participating agents, and it must happen dynamically, as it is hard to predict the effort associated with the exploration of some part of the search space.
We describe and provide an initial experimental assessment of an imple- mentation of a work stealing-based approach to distributed CSP solving, which relies on multiple back-ends for the distributed computing mecha- nisms – from the multicore CPU to supercomputer clusters running MPI or other interprocess communication platforms.

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## Towards constraint-informed information systems

Fonte: IEEE
Publicador: IEEE

Tipo: Artigo de Revista Científica

POR

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Declarative techniques such as Constraint Programming are very useful in modeling complex requirements. They have the added benefit of being executable specifications and, when properly tuned, high-performance ones. In this paper we argue that Information Systems ought to include constraint-based techniques in their design and implementation. We support this claim by introducing tools based on constraint programming, which we apply to an actual use-case: the academic timetable construction and maintenance problem, as developed at the University of Evora. The system we built was implemented using the GNU Prolog language. Moreover, Constraints have the potential to describe global properties that a model must observe, which makes them a semantically very interesting extension to the capabilities of present model-driven techniques and tools.

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## Geolocation of Data in the Cloud

Fonte: Escola de Pós-Graduação Naval
Publicador: Escola de Pós-Graduação Naval

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

35.91%

#Security#Legal Aspects#Measurement#Experimentation#Cloud storage#storage security#data availability#provable data possession#proof of data geolocation

We introduce and analyze a general framework for authentically
binding data to a location while providing strong
assurances against cloud storage providers that (either accidentally
or maliciously) attempt to re-locate cloud data.
We then evaluate a preliminary solution in this framework
that combines constraint-based host geolocation with proofs
of data possession, called constraint-based data geolocation
(CBDG). We evaluate CBDG using a combination of experiments
with PlanetLab and real cloud storage services,
demonstrating that we can bind fetched data to the location
originally hosting it with high precision. We geolocate
data hosted on the majority of our PlanetLab targets to regions
no larger than 118,000 km2, and we geolocate data
hosted on Amazon S3 to an area no larger than 12,000 km2,
sufficiently small to identify the state or service region.; Partial support for this work was provided by the National Science Foundation under award No. 1143573.

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## What Matters to African Firms? The Relevance of Perceptions Data

Fonte: World Bank, Washington, DC
Publicador: World Bank, Washington, DC

Tipo: Publications & Research :: Policy Research Working Paper; Publications & Research

ENGLISH

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#ACCESS TO CREDIT#ACCESS TO FINANCE#ACCOUNTING#BINDING CONSTRAINT#BINDING CONSTRAINTS#BRIBE#BRIBES#BUSINESS CLIMATE#BUSINESS CLIMATES#BUSINESS ENVIRONMENT#BUSINESS OPPORTUNITIES

Can perceptions data help us understand
investment climate constraints facing the private sector?
Or do firms simply complain about everything? In this paper,
the authors provide a picture of how firms' views on
constraints differ across countries in Sub-Saharan Africa.
Using the World Bank's Enterprise Surveys database,
they find that reported constraints reflect country
characteristics and vary systematically by level of
income-the most elemental constraints to doing business
(power, access to finance, ability to plan ahead) appear to
be most binding at low levels of income. As countries
develop and these elemental constraints are relaxed,
governance-related constraints become more problematic. As
countries move further up the income scale and the state
becomes more capable, labor regulation is perceived to be
more of a problem-business is just one among several
important constituencies. The authors also consider whether
firm-level characteristics-such as size, ownership, exporter
status, and firms' own experience-affect firms'
views on the severity of constraints. They find that...

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## DSM-PM2 adequacy for distributed constraint programming

Fonte: Universidade de Évora
Publicador: Universidade de Évora

Tipo: Dissertação de Mestrado

ENG

Relevância na Pesquisa

36.02%

As Redes de alta velocidade e o melhoramento rápido da performance dos microprocessadores fazem das redes de computadores um veículo apelativo para computação paralela. Não é preciso hardware especial para usar computadores paralelos e o sistema resultante é extensível e facilmente alterável. A programação por restrições é um paradigma de programação em que as relações entre as variáveis pode ser representada por restrições. As restrições diferem das primitivas comuns das outras linguagens de programação porque, ao contrário destas, não específica uma sequência de passos a executar mas antes a definição das propriedades para encontrar as soluções de um problema específico. As bibliotecas de programação por restrições são úteis visto elas não requerem que os programadores tenham que aprender novos skills para uma nova linguagem mas antes proporcionam ferramentas de programação declarativa para uso em sistemas convencionais. A tecnologia de Memoria Partilhada Distribuída (Distributed Shared Memory) apresenta-se como uma ferramenta para uso em aplicações distribuídas em que a informação individual partilhada pode ser acedida diretamente. Nos sistemas que suportam esta tecnologia os dados movem-se entre as memórias principais dos diversos nós de um cluster. Esta tecnologia poupa o programador às preocupações de passagem de mensagens onde ele teria que ter muito trabalho de controlo do comportamento do sistema distribuído. Propomos uma arquitetura orientada para a distribuição de Programação por Restrições que tenha os mecanismos da propagação e da procura local como base sobre um ambiente CC-NUMA distribuído usando memória partilhada distribuída. Os principais objetivos desta dissertação podem ser sumarizados em: - Desenvolver um sistema resolvedor de restrições...

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## Hybrid tractability of soft constraint problems

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 24/08/2010

Relevância na Pesquisa

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The constraint satisfaction problem (CSP) is a central generic problem in
computer science and artificial intelligence: it provides a common framework
for many theoretical problems as well as for many real-life applications. Soft
constraint problems are a generalisation of the CSP which allow the user to
model optimisation problems. Considerable effort has been made in identifying
properties which ensure tractability in such problems. In this work, we
initiate the study of hybrid tractability of soft constraint problems; that is,
properties which guarantee tractability of the given soft constraint problem,
but which do not depend only on the underlying structure of the instance (such
as being tree-structured) or only on the types of soft constraints in the
instance (such as submodularity). We present several novel hybrid classes of
soft constraint problems, which include a machine scheduling problem,
constraint problems of arbitrary arities with no overlapping nogoods, and the
SoftAllDiff constraint with arbitrary unary soft constraints. An important tool
in our investigation will be the notion of forbidden substructures.; Comment: A full version of a CP'10 paper, 26 pages

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## Improved Parameterized Algorithms for Constraint Satisfaction

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

35.91%

For many constraint satisfaction problems, the algorithm which chooses a
random assignment achieves the best possible approximation ratio. For instance,
a simple random assignment for {\sc Max-E3-Sat} allows 7/8-approximation and
for every $\eps >0$ there is no polynomial-time ($7/8+\eps$)-approximation
unless P=NP. Another example is the {\sc Permutation CSP} of bounded arity.
Given the expected fraction $\rho$ of the constraints satisfied by a random
assignment (i.e. permutation), there is no $(\rho+\eps)$-approximation
algorithm for every $\eps >0$, assuming the Unique Games Conjecture (UGC).
In this work, we consider the following parameterization of constraint
satisfaction problems. Given a set of $m$ constraints of constant arity, can we
satisfy at least $\rho m +k$ constraint, where $\rho$ is the expected fraction
of constraints satisfied by a random assignment? {\sc Constraint Satisfaction
Problems above Average} have been posed in different forms in the literature
\cite{Niedermeier2006,MahajanRamanSikdar09}. We present a faster parameterized
algorithm for deciding whether $m/2+k/2$ equations can be simultaneously
satisfied over ${\mathbb F}_2$. As a consequence, we obtain $O(k)$-variable
bikernels for {\sc boolean CSPs} of arity $c$ for every fixed $c$...

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## Filtering Algorithms for the Multiset Ordering Constraint

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 03/03/2009

Relevância na Pesquisa

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Constraint programming (CP) has been used with great success to tackle a wide
variety of constraint satisfaction problems which are computationally
intractable in general. Global constraints are one of the important factors
behind the success of CP. In this paper, we study a new global constraint, the
multiset ordering constraint, which is shown to be useful in symmetry breaking
and searching for leximin optimal solutions in CP. We propose efficient and
effective filtering algorithms for propagating this global constraint. We show
that the algorithms are sound and complete and we discuss possible extensions.
We also consider alternative propagation methods based on existing constraints
in CP toolkits. Our experimental results on a number of benchmark problems
demonstrate that propagating the multiset ordering constraint via a dedicated
algorithm can be very beneficial.

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## Discovering Archipelagos of Tractability for Constraint Satisfaction and Counting

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

35.91%

The Constraint Satisfaction Problem (CSP) is a central and generic
computational problem which provides a common framework for many theoretical
and practical applications. A central line of research is concerned with the
identification of classes of instances for which CSP can be solved in
polynomial time; such classes are often called "islands of tractability." A
prominent way of defining islands of tractability for CSP is to restrict the
relations that may occur in the constraints to a fixed set, called a constraint
language, whereas a constraint language is conservative if it contains all
unary relations. This paper addresses the general limit of the mentioned
tractability results for CSP and #CSP, that they only apply to instances where
all constraints belong to a single tractable language (in general, the union of
two tractable languages isn't tractable). We show that we can overcome this
limitation as long as we keep some control of how constraints over the various
considered tractable languages interact with each other. For this purpose we
utilize the notion of a \emph{strong backdoor} of a CSP instance, as introduced
by Williams et al. (IJCAI 2003), which is a set of variables that when
instantiated moves the instance to an island of tractability...

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## Parameterized Algorithms for Constraint Satisfaction Problems Above Average with Global Cardinality Constraints

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 02/11/2015

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Given a constraint satisfaction problem (CSP) on $n$ variables, $x_1, x_2,
\dots, x_n \in \{\pm 1\}$, and $m$ constraints, a global cardinality constraint
is in the form of $\sum_{i = 1}^{n} x_i = (1-2p)n$, where $p \in (\Omega(1), 1
- \Omega(1))$ and $pn$ is an integer. Let $AVG$ be the expected number of
constraints satisfied by randomly choosing an assignment to $x_1, x_2, \dots,
x_n$, complying with the global cardinality constraint. The CSP above average
with the global cardinality constraint problem asks whether there is an
assignment (complying with the cardinality constraint) that satisfies more than
$(AVG+t)$ constraints, where $t$ is an input parameter.
In this paper, we present an algorithm that finds out a valid assignment
satisfying more than $(AVG+t)$ constraints (if there exists one) in time
$(2^{O(t^2)} + n^{O(d)})$. Therefore, the CSP above average with the global
cardinality constraint problem is fixed-parameter tractable.; Comment: 36 pages

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## Clustering by soft-constraint affinity propagation: Applications to gene-expression data

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

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#Quantitative Biology - Quantitative Methods#Condensed Matter - Statistical Mechanics#Physics - Data Analysis, Statistics and Probability

Motivation: Similarity-measure based clustering is a crucial problem
appearing throughout scientific data analysis. Recently, a powerful new
algorithm called Affinity Propagation (AP) based on message-passing techniques
was proposed by Frey and Dueck \cite{Frey07}. In AP, each cluster is identified
by a common exemplar all other data points of the same cluster refer to, and
exemplars have to refer to themselves. Albeit its proved power, AP in its
present form suffers from a number of drawbacks. The hard constraint of having
exactly one exemplar per cluster restricts AP to classes of regularly shaped
clusters, and leads to suboptimal performance, {\it e.g.}, in analyzing gene
expression data. Results: This limitation can be overcome by relaxing the AP
hard constraints. A new parameter controls the importance of the constraints
compared to the aim of maximizing the overall similarity, and allows to
interpolate between the simple case where each data point selects its closest
neighbor as an exemplar and the original AP. The resulting soft-constraint
affinity propagation (SCAP) becomes more informative, accurate and leads to
more stable clustering. Even though a new {\it a priori} free-parameter is
introduced, the overall dependence of the algorithm on external tuning is
reduced...

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## An n-ary Constraint for the Stable Marriage Problem

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 01/08/2013

Relevância na Pesquisa

35.94%

We present an n-ary constraint for the stable marriage problem. This
constraint acts between two sets of integer variables where the domains of
those variables represent preferences. Our constraint enforces stability and
disallows bigamy. For a stable marriage instance with $n$ men and $n$ women we
require only one of these constraints, and the complexity of enforcing
arc-consistency is $O(n^2)$ which is optimal in the size of input. Our
computational studies show that our n-ary constraint is significantly faster
and more space efficient than the encodings presented in \cite{cp01}. We also
introduce a new problem to the constraint community, the sex-equal stable
marriage problem.; Comment: 7 pages. The Fifth Workshop on Modelling and Solving Problems with
Constraints, held at the 19th International Joint Conference on Artificial
Intelligence (IJCAI 2005)

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## Consistency Techniques for Flow-Based Projection-Safe Global Cost Functions in Weighted Constraint Satisfaction

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 18/01/2014

Relevância na Pesquisa

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Many combinatorial problems deal with preferences and violations, the goal of
which is to find solutions with the minimum cost. Weighted constraint
satisfaction is a framework for modeling such problems, which consists of a set
of cost functions to measure the degree of violation or preferences of
different combinations of variable assignments. Typical solution methods for
weighted constraint satisfaction problems (WCSPs) are based on branch-and-bound
search, which are made practical through the use of powerful consistency
techniques such as AC*, FDAC*, EDAC* to deduce hidden cost information and
value pruning during search. These techniques, however, are designed to be
efficient only on binary and ternary cost functions which are represented in
table form. In tackling many real-life problems, high arity (or global) cost
functions are required. We investigate efficient representation scheme and
algorithms to bring the benefits of the consistency techniques to also high
arity cost functions, which are often derived from hard global constraints from
classical constraint satisfaction. The literature suggests some global cost
functions can be represented as flow networks, and the minimum cost flow
algorithm can be used to compute the minimum costs of such networks in
polynomial time. We show that naive adoption of this flow-based algorithmic
method for global cost functions can result in a stronger form of null-inverse
consistency. We further show how the method can be modified to handle cost
projections and extensions to maintain generalized versions of AC* and FDAC*
for cost functions with more than two variables. Similar generalization for the
stronger EDAC* is less straightforward. We reveal the oscillation problem when
enforcing EDAC* on cost functions sharing more than one variable. To avoid
oscillation...

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## Dictionary learning under global sparsity constraint

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

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A new method is proposed in this paper to learn overcomplete dictionary from
training data samples. Differing from the current methods that enforce similar
sparsity constraint on each of the input samples, the proposed method attempts
to impose global sparsity constraint on the entire data set. This enables the
proposed method to fittingly assign the atoms of the dictionary to represent
various samples and optimally adapt to the complicated structures underlying
the entire data set. By virtue of the sparse coding and sparse PCA techniques,
a simple algorithm is designed for the implementation of the method. The
efficiency and the convergence of the proposed algorithm are also theoretically
analyzed. Based on the experimental results implemented on a series of signal
and image data sets, it is apparent that our method performs better than the
current dictionary learning methods in original dictionary recovering, input
data reconstructing, and salient data structure revealing.; Comment: 27 pages, 9 figures, 1 table

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## Constraint satisfaction parameterized by solution size

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

35.96%

In the constraint satisfaction problem (CSP) corresponding to a constraint
language (i.e., a set of relations) $\Gamma$, the goal is to find an assignment
of values to variables so that a given set of constraints specified by
relations from $\Gamma$ is satisfied. The complexity of this problem has
received substantial amount of attention in the past decade. In this paper we
study the fixed-parameter tractability of constraint satisfaction problems
parameterized by the size of the solution in the following sense: one of the
possible values, say 0, is "free," and the number of variables allowed to take
other, "expensive," values is restricted. A size constraint requires that
exactly $k$ variables take nonzero values. We also study a more refined version
of this restriction: a global cardinality constraint prescribes how many
variables have to be assigned each particular value. We study the parameterized
complexity of these types of CSPs where the parameter is the required number
$k$ of nonzero variables. As special cases, we can obtain natural and
well-studied parameterized problems such as Independent Set, Vertex Cover,
d-Hitting Set, Biclique, etc.
In the case of constraint languages closed under substitution of constants,
we give a complete characterization of the fixed-parameter tractable cases of
CSPs with size constraints...

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## Materialized view selection under the maintenance time constraint

Fonte: Elsevier
Publicador: Elsevier

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

36.12%

#Keywords: Algorithms#Approximation theory#Constraint theory#Data mining#Decision theory#Heuristic methods#Problem solving#Incremental maintenance#Maintenance time constraint#Data warehouses Data integration#Design of data warehouse

A data warehouse is a data repository which collects and maintains a large amount of data from multiple distributed, autonomous and possibly heterogeneous data sources. Often the data is stored in the form of materialized views in order to provide fast access to the integrated data. One of the most important decisions in designing a data warehouse is the selection of views for materialization. The objective is to select an appropriate set of views that minimizes the total query response time with the constraint that the total maintenance time for these materialized views is within a given bound. This view selection problem is totally different from the view selection problem under the disk space constraint. In this paper the view selection problem under the maintenance time constraint is investigated. Two efficient, heuristic algorithms for the problem are proposed. The key to devising the proposed algorithms is to define good heuristic functions and to reduce the problem to some well-solved optimization problems. As a result, an approximate solution of the known optimization problem will give a feasible solution of the original problem.

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