Marcelo Ladeira

Marcelo Ladeira
University of Brasília | UnB · Department of Computer Science

About

76
Publications
24,436
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561
Citations

Publications

Publications (76)
Conference Paper
Full-text available
The performance of multiobjective algorithms varies across problems, making it hard to develop new algorithms or apply existing ones to new problems. To simplify the development and application of new multiobjective algorithms, there has been an increasing interest in their automatic design from component parts. These automatically designed metaheu...
Article
The Resource Allocation approach (RA) improves the performance of MOEA/D by maintaining a big population and updating few solutions each generation. However, most of the studies on RA generally focused on the properties of different Resource Allocation metrics. Thus, it is still uncertain what the main factors are that lead to increments in perform...
Preprint
Full-text available
The Resource Allocation approach (RA) improves the performance of MOEA/D by maintaining a big population and updating few solutions each generation. However, most of the studies on RA generally focused on the properties of different Resource Allocation metrics. Thus, it is still uncertain what the main factors are that lead to increments in perform...
Conference Paper
Full-text available
This paper presents a case study based on the CRISP-DM Model and the use of Text Mining tools and techniques to automate the Passive Transparency process at the BrazilianMinistry of Mines and Energy. Thus, a Machine Learning Model is proposed to predict the class of the technical unit responsible for the data/information requested by citizens.Throu...
Chapter
Gliomas are the most common malignant brain tumors that are treated with chemoradiotherapy and surgery. Magnetic Resonance Imaging (MRI) is used by radiotherapists to manually segment brain lesions and to observe their development throughout the therapy. The manual image segmentation process is time-consuming and results tend to vary among differen...
Chapter
Finding good solutions for Multi-objective Problems (MOPs) is considered a hard problem, especially when considering MOPs with constraints. Thus, most of the works in the context of MOPs do not explore in-depth how different constraints affect the performance of MOP solvers. Here, we focus on exploring the effects of different Constraint Handling T...
Preprint
Full-text available
Finding good solutions for Multi-objective Optimization (MOPs) Problems is considered a hard problem, especially when considering MOPs with constraints. Thus, most of the works in the context of MOPs do not explore in-depth how different constraints affect the performance of MOP solvers. Here, we focus on exploring the effects of different Constrai...
Preprint
Full-text available
Recent studies on resource allocation suggest that some subproblems are more important than others in the context of the MOEA/D, and that focusing on the most relevant ones can consistently improve the performance of that algorithm. These studies share the common characteristic of updating only a fraction of the population at any given iteration of...
Preprint
Full-text available
Gliomas are the most common malignant brain tumors that are treated with chemoradiotherapy and surgery. Magnetic Resonance Imaging (MRI) is used by radiotherapists to manually segment brain lesions and to observe their development throughout the therapy. The manual image segmentation process is time-consuming and results tend to vary among differen...
Conference Paper
Full-text available
The level of Maturity in Process Management (MPM) is directly related to the efficiency and value creation of an organization. For this reason, various maturity models have been proposed in recent years, most of them focused on the private sector. However, the assessment of MPM levels in the public sector requires specific criteria. In this study,...
Chapter
Full-text available
One of the main algorithms for solving Multi-Objective Optimization Problems is the Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D). It is characterized by decomposing the multiple objectives into a large number of single-objective subproblems, and then solving these subproblems in parallel. Usually, these subproblems are con...
Conference Paper
The analysis of electroencephalogram (EEG) waves is of critical importance for the diagnosis of sleep disorders, such as sleep apnea and insomnia, besides that, seizures, epilepsy, head injuries, dizziness, headaches and brain tumors. In this context, one important task is the identification of visible structures in the EEG signal, such as sleep sp...
Preprint
Full-text available
The analysis of electroencephalogram (EEG) waves is of critical importance for the diagnosis of sleep disorders, such as sleep apnea and insomnia, besides that, seizures, epilepsy, head injuries, dizziness, headaches and brain tumors. In this context, one important task is the identification of visible structures in the EEG signal, such as sleep sp...
Article
This article demonstrates a study on Market Basket Analysis of a financial institution, showing rules of personal consumer association of the state of São Paulo. A concept about three association algorithms is presented, but a study with only one is performed. The paper is divided into an introduction, describing a brief account of the reason for c...
Article
Full-text available
This paper presents a study of rates of dropout from Brazilian degree courses, based on data provided by the National Institute for Educational Studies and Research “Anísio Teixeira” (INEP) and a case study carried out at the University of Brasilia (UnB). Dropout was calculated by tracking the status of each student between 2010 and 2014 in the eig...
Conference Paper
With the expanding diversity of database technologies and database sizes, it is becoming increasingly hard to identify similar relational databases among many large databases stored in different Database Management Systems (DBMS). Therefore, we propose to use data mining techniques to automatically identify similar structures of relational database...
Conference Paper
The Observatory of Public Spending (ODP, in Portuguese) is a special unit of Brazil's Ministry of Transparency and Office of the Comptroller-General (CGU, in Portuguese) responsible for gathering managerial and audit information to support the work of its auditors. One of the most important tasks of this unit is to monitor government suppliers who...
Conference Paper
Full-text available
We perform an experimental study about the effectof the tournament size parameter from the Tournament Selectionoperator. Tournament Selection is a classic operator for GeneticAlgorithms and Genetic Programming. It is simple to implementand has only one control parameter, thetournament size.Eventhough it is commonly used, most practitioners still re...
Chapter
NoSQL databases offer flexibility in the data model. The document-based databases may have some data models built with embedded documents, and others made with referenced documents. The challenge lies in choosing the structure of the data. This paper proposes a study to analyze if different data models can have an impact on the performance of datab...
Article
Full-text available
This paper is an extended version of the paper originally presented at the International Conference on Machine Learning and Applications (ICMLA 2016), which proposes the construction of classifiers, based on the application of machine learning techniques, to identify defaulting clients with credit recovery potential. The study was carried out in 3...
Conference Paper
Full-text available
A técnica estatística de Análise de Sobrevivência e a mineração de regras de associação via algoritmo Apriori foram aplicadas neste artigo, usando registros dos alunos dos cursos de Bacharelado em Ciência da Computação, Licenciatura em Computação, Engenharia de Computação e Engenharia de Software da Universidade de Brasília (UnB). Esse artigo verif...
Conference Paper
This article presents the partial results of a research, which was used advanced programming with Analytic Hierarchy Process (AHP) using Expert Choice software to identify critical components of Information Technology (IT) that impact an organization and its relationship with the strategic objectives. The study is a qualitative and quantitative app...
Conference Paper
Probabilistic OWL (PR-OWL) improves the Web Ontology Language (OWL) with the ability to treat uncertainty using Multi-Entity Bayesian Networks (MEBN). PR-OWL 2 presents a better integration with OWL and its underlying logic, allowing the creation of ontologies with probabilistic and deterministic parts. However, there are scalability problems since...
Conference Paper
Full-text available
The probabilistic ontology language PR-OWL (Probabilistic OWL) uses Multi-Entity Bayesian Networks (MEBN), an extension of Bayesian networks with first-order logic, to add the ability to deal with uncertainty to OWL, the main language of the Semantic Web. A second version, PR-OWL 2, was proposed to allow the construction of hybrid ontologies, conta...
Chapter
The use of noun phrases as descriptors for text mining vectors has been proposed to overcome the poor semantic of the traditional bag-of-words (BOW). However, the solutions found in the literature are unsatisfactory, mainly due to the use of static definitions for noun phrases and the fact that noun phrases per se do not enable an adequate relevanc...
Article
This paper presents a case study of machine learning applied to measure the risk of corruption of civil servants using political party affiliation data. Initially, a statistical hypothesis test verified the dependency between corruption and political party affiliation. Then, we constructed datasets with standardization and three different discrimin...
Conference Paper
This work describes an opinion mining application over a dataset extracted from the web and composed of reviews with several Internet slangs, abbreviations and typo errors. Opinion mining is a study field that tries to identify and classify subjectivity, such as opinions, emotions or sentiments in natural language. In this research, 759.176 Portugu...
Conference Paper
Full-text available
Discovering how people are related contributes to accurately assessing several scenarios within a criminal investigation. If two people have family ties, such as, brothers or cousins, for example, and one of them has been involved in criminal activities, there is a high probability that the other has also been involved in these same or other simila...
Chapter
Several approaches have been proposed for dealing with uncertainty in the Semantic Web (SW). Although probabilistic ontologies (PO) is one of the most promising approach to model uncertainty in ontologies, no support has been offered to ontological engineers on how to create this more complex type of ontologies. This task has proven to be extremely...
Article
Full-text available
Although various formalisms for building probabilistic ontologies (POs) have been developed, this area still lacks adequate methodologies to guide the experts in the development and application of these ontologies. The Uncertainty Reasoning Process for Semantic Technology (URP-ST) has been proposed to remedy this deficiency by providing a process f...
Article
Full-text available
Understanding the mechanisms and patterns of earthquake occurrence is of crucial importance for assessing and mitigating the seismic risk. In this work we analyze the viability of using Evolutionary Computation (EC) as a means of generating models for the occurrence of earthquakes. Our proposal is made in the context of the "Collaboratory for the S...
Conference Paper
This paper focuses on the incorporation of the Markov Logic Network (MLN) formalism as a plug-in for UnBBayes, a Java framework for probabilistic reasoning based on graphical models. MLN is a formal- ism for probabilistic reasoning which combines the capacity of dealing with uncertainty tolerating imperfections and contradictory knowledge based a M...
Conference Paper
Although several languages have been proposed for dealing with uncertainty in the Semantic Web (SW), almost no support has been given to ontological engineers on how to create such probabilistic ontologies (PO). This task of modeling POs has proven to be extremely difficult and hard to replicate. This paper presents the first tool in the world to i...
Chapter
Full-text available
This Chapter invites you to understand the problems beneath the classical models (see Section 2), and to appreciate some fundamental theoretical principles and methods for modeling probabilistic ontologies (see Section 3), presenting you with a step-by-step construction of a simple probabilistic ontology for image-based vehicle identification using...
Chapter
Full-text available
Ontologies provide the “semantic glue” to enable knowledge sharing among systems collaborating in radical information sharing domains: open world domains in which Anyone can say Anything about Any topic (AAA), and entities may not have unique names. Traditional ontologies fail to provide adequate support for uncertainty, a ubiquitous characteristic...
Conference Paper
Full-text available
To cope with society's demand for transparency and corruption prevention, the Brazilian Office of the Comptroller General (CGU) has carried out a number of actions, including: awareness campaigns aimed at the private sector; campaigns to educate the public; research initiatives; and regular inspections and audits of municipalities and states. Altho...
Article
Full-text available
Bayesian network is a graphical model appropriated to represent and to analyze uncertainty, knowledge and beliefs contained implicitly in the data. In this paper we propose the XPC algorithm for structural learning in Bayesian networks using decomposable metrics in families (a variable and its parents) in order to obtain the maximum-score network....
Conference Paper
Full-text available
No Brasil, a classificação do acabamento de gordura de carcaças bovinas é regulamentado pela Portaria de n.º 612 de 05/12/1989 do Ministério da Agricultura. Esse processo é realizado por meio da observação visual e subjetiva através da análise de regiões predefinidas, feita por um profissional habilitado, durante o processo de abate nas indústrias...
Conference Paper
The quest for principled approaches to represent and reason under uncertainty in the Semantic Web (SW) is a very active research subject. Recently, the World Wide Web Consortium (W3C) created the Uncertainty Reasoning for the World Wide Web Incubator Group - URW3-XG [Laskey, K.J. et al., 2007] to better define the challenge of reasoning with and re...
Conference Paper
Full-text available
One of the major weaknesses of current research on the Semantic Web {(SW)} is the lack of proper means to represent and reason with uncertainty. A number of recent efforts from the {SW} community, the {W3C,} and others have recently emerged to address this gap. Such efforts have the positive side effect of bringing together two fields of research t...
Conference Paper
As the work with semantics and services grows more ambitious in the Semantic Web community, there is an increasing appreciation on the need for principled approaches for representing and reasoning under uncertainty. Reacting to this trend, the World Wide Web Consortium (W3C) has recently created the Uncertainty Reasoning for the World Wide Web Incu...
Article
Full-text available
Knowledge Discovery in Databases (KDD), as any organizational process, is carried out beneath a Knowledge Management (KM) model adopted (even informally) by a corporation. KDD is grossly described in three steps: pre-processing, data mining, and post-processing. The latter is mainly related to the task of transforming in knowledge the patterns issu...
Conference Paper
This paper describes the UnBBayes. This software supports the graphical edition of Bayesian network, influence diagram, and multiple sectioned Bayesian network. The learning of either the structure (topology) or the parameters (probabilities) of Bayesian networks, based on search and measures algorithms (K2 or B) or conditional independence (Cheng-...
Article
AMPLIA is a multi-agent intelligent learning environment designed to support training of diagnostic reasoning and modelling of domains with complex and uncertain knowledge. AMPLIA focuses on the medical area. It is a system that deals with uncertainty under the Bayesian network approach, where learner-modelling tasks will consist of creating a Baye...
Article
Full-text available
This paper presents the SEAMED framework. Real domains into environment with uncertainty can be model with this framework, as follows. The theory of probabilities is used to model and to treat the inherent uncertainty of the domain. The domain is modeled with a set of random variables. A directed link from a random variable to another one represent...
Article
Full-text available
Resumo: Uma forma fundamentada de se lidar com incerteza é utilizar a evidência disponível (informação sobre o estado atual de uma variável aleatória) para refinar as estimativas das probabilidades associadas às demais variáveis de interesse. No entanto, as relações probabilísticas entre variáveis aleatórias são relacionamentos dinâmicos que se alt...
Article
Full-text available
The machine­learning approach to websites classification belongs to the class of multi­label problems, i.e., a single document can be labeled with more than one category, which is the harder and less studied class. This article proposes a new algorithm, based on the Minimum Description Length principle and on the Adaptive Huffman coding, which can...
Article
Full-text available
AMPLIA is an Intelligent Learning Multi-Agent Environment. It is designed to support training of diagnostic reasoning and modeling of domains with complex and uncertain knowledge. AMPLIA focuses on the medical area. It is a system that deals with uncertainty under the Bayesian network approach, where learner modeling tasks will consist of creating...
Article
Full-text available
This paper presents a Java API called NeuralNetworkToolkit. This API was conceived to perform non-linear multiple regression, on a black-box approach, using a multiple-layer perceptron artificial neural network with Levenberg-Marquardt and backpropagation training. This algorithm offers faster training performance than the standard backpropagation...
Article
Full-text available
Bayesian network is a graphical model appropriated to represent and to analyze uncertainty, knowledge and beliefs contained implicitly in the data. In this paper we propose the XPC algorithm for structural learning in Bayesian networks using decomposable metrics in families (a variable and its parents) in order to obtain the maximum-score network....
Article
Full-text available
Bayesian Networks are efficient mechanisms for data analysis that present relationships of temporal precedence. A Bayesian Network has two components: a graphical structure and the numeric parameters. One can learn automatically from a database both the graphical structure and the numeric parameters. This work provides theoretical base and proposes...
Article
Full-text available
Harmony Search (HS) is an optimization algorithm that mimicks the improvisation process of jazz musicians. It was originally conceived as an derivative-free method. But what if it is feasible to evaluate the gradient of the objective function? We believe that any optimization algorithm should use all information available. In this article, we descr...
Article
Full-text available
The Brazilian bovine carcass classification process is regulated by the Brazilian Agriculture Ministry decree number 612 of December 05, 1989. Although the usual bovine carcass classification process is carried out by a qualified technician it is very subjective because it is based on a visual inspection of predefined carcass areas during the bovin...
Article
Full-text available
Spamming has been a great problem to internet users and service providers. Recent research points towards the employment of machine learning algorithms to spam filtering. However, many works that have been done in the area do not recognize the dynamic aspect of spam, rendering the filtering process solely as a text categorization problem. This work...