Utilizando conceitos como descritores de textos para o processo de identificação de conglomerados (clustering) de documentos

A descoberta e a análise de conglomerados textuais são processos muito importantes para a estruturação, organização e a recuperação de informações, assim como para a descoberta de conhecimento. Isto porque o ser humano coleta e armazena uma quantidade muito grande de dados textuais, que necessitam ser vasculhados, estudados, conhecidos e organizados de forma a fornecerem informações que lhe dêem o conhecimento para a execução de uma tarefa que exija a tomada de uma decisão. É justamente nesse ponto que os processos de descoberta e de análise de conglomerados (clustering) se insere, pois eles auxiliam na exploração e análise dos dados, permitindo conhecer melhor seu conteúdo e inter-relações. No entanto, esse processo, por ser aplicado em textos, está sujeito a sofrer interferências decorrentes de problemas da própria linguagem e do vocabulário utilizado nos mesmos, tais como erros ortográficos, sinonímia, homonímia, variações morfológicas e similares. Esta Tese apresenta uma solução para minimizar esses problemas, que consiste na utilização de “conceitos” (estruturas capazes de representar objetos e idéias presentes nos textos) na modelagem do conteúdo dos documentos. Para tanto, são apresentados os conceitos e as áreas relacionadas com o tema, os trabalhos correlatos (revisão bibliográfica), a metodologia proposta e alguns experimentos que permitem desenvolver determinados argumentos e comprovar algumas hipóteses sobre a proposta. As conclusões principais desta Tese indicam que a técnica de conceitos possui diversas vantagens, dentre elas a utilização de uma quantidade muito menor, porém mais representativa, de descritores para os documentos, o que torna o tempo e a complexidade do seu processamento muito menor, permitindo que uma quantidade muito maior deles seja analisada. Outra vantagem está no fato de o poder de expressão de conceitos permitir que os usuários analisem os aglomerados resultantes muito mais facilmente e compreendam melhor seu conteúdo e forma. Além do método e da metodologia proposta, esta Tese possui diversas contribuições, entre elas vários trabalhos e artigos desenvolvidos em parceria com outros pesquisadores e colegas.

Teacher education in Portugal: analysing changes using ATEE-RDC19 scenario methodology

This paper presents an overview of the development of teacher education in Portugal since the Revolution of 25 April 1974, which brought the country to democracy. Making use of the scenario model created by the ATEE-RDC19, it is an attempt to make clearer the hidden philosophies underlying the changes that are undertaken and show how teacher education has evolved from a romantic and idealistic social vision towards an ideology dictated by economic and selfish interests.

Contribuições aos Processos de Clustering com Base em Métricas não-Euclidianas

In this work we present a new clustering method that groups up points of a data set in classes. The method is based in a algorithm to link auxiliary clusters that are obtained using traditional vector quantization techniques. It is described some approaches during the development of the work that are based in measures of distances or dissimilarities (divergence) between the auxiliary clusters. This new method uses only two a priori information, the number of auxiliary clusters Na and a threshold distance dt that will be used to decide about the linkage or not of the auxiliary clusters. The number os classes could be automatically found by the method, that do it based in the chosen threshold distance dt, or it is given as additional information to help in the choice of the correct threshold. Some analysis are made and the results are compared with traditional clustering methods. In this work different dissimilarities metrics are analyzed and a new one is proposed based on the concept of negentropy. Besides grouping points of a set in classes, it is proposed a method to statistical modeling the classes aiming to obtain a expression to the probability of a point to belong to one of the classes. Experiments with several values of Na e dt are made in tests sets and the results are analyzed aiming to study the robustness of the method and to consider heuristics to the choice of the correct threshold. During this work it is explored the aspects of information theory applied to the calculation of the divergences. It will be explored specifically the different measures of information and divergence using the Rényi entropy. The results using the different metrics are compared and commented. The work also has appendix where are exposed real applications using the proposed method

Uma Aplicação do Algoritmo QT Clustering para Marcação Colaborativa de Pontos Perigosos em Vias Públicas

This work proposes a collaborative system for marking dangerous points in the transport routes and generation of alerts to drivers. It consisted of a proximity warning system for a danger point that is fed by the driver via a mobile device equipped with GPS. The system will consolidate data provided by several different drivers and generate a set of points common to be used in the warning system. Although the application is designed to protect drivers, the data generated by it can serve as inputs for the responsible to improve signage and recovery of public roads

Hybrid evolutionary algorithm for the Capacitated Centered Clustering Problem

The Capacitated Centered Clustering Problem (CCCP) consists of defining a set of p groups with minimum dissimilarity on a network with n points. Demand values are associated with each point and each group has a demand capacity. The problem is well known to be NP-hard and has many practical applications. In this paper, the hybrid method Clustering Search (CS) is implemented to solve the CCCP. This method identifies promising regions of the search space by generating solutions with a metaheuristic, such as Genetic Algorithm, and clustering them into clusters that are then explored further with local search heuristics. Computational results considering instances available in the literature are presented to demonstrate the efficacy of CS. (C) 2010 Elsevier Ltd. All rights reserved.

Artificial neural networks and clustering techniques applied in the reconfiguration of distribution systems

One objective of the feeder reconfiguration problem in distribution systems is to minimize the power losses for a specific load. For this problem, mathematical modeling is a nonlinear mixed integer problem that is generally hard to solve. This paper proposes an algorithm based on artificial neural network theory. In this context, clustering techniques to determine the best training set for a single neural network with generalization ability are also presented. The proposed methodology was employed for solving two electrical systems and presented good results. Moreover, the methodology can be employed for large-scale systems in real-time environment.

Structural damage detection by fuzzy clustering

The development of strategies for structural health monitoring (SHM) has become increasingly important because of the necessity of preventing undesirable damage. This paper describes an approach to this problem using vibration data. It involves a three-stage process: reduction of the time-series data using principle component analysis (PCA), the development of a data-based model using an auto-regressive moving average (ARMA) model using data from an undamaged structure, and the classification of whether or not the structure is damaged using a fuzzy clustering approach. The approach is applied to data from a benchmark structure from Los Alamos National Laboratory, USA. Two fuzzy clustering algorithms are compared: fuzzy c-means (FCM) and Gustafson-Kessel (GK) algorithms. It is shown that while both fuzzy clustering algorithms are effective, the GK algorithm marginally outperforms the FCM algorithm. (C) 2008 Elsevier Ltd. All rights reserved.

A new scenario of bioprospecting of Hymenoptera venoms through proteomic approach

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Scenario of the spread of the invasive species Zaprionus indianus Gupta, 1970 (Diptera, Drosophilidae) in Brazil

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

New Insight into the Mechanism of Action of Wasp Mastoparan Peptides: Lytic Activity and Clustering Observed with Giant Vesicles

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The origin of the first and third generation fermion massesin a technicolor scenario

We argue that the masses of the first and third fermionic generations, which are respectively of the order of a few MeV up to a hundred GeV, originate from a dynamical symmetry breaking mechanism leading to masses of the order alphamu, where alpha is a small coupling constant, and mu, in the case of the first fermionic generation, is the scale of the dynamical quark mass (approximate to250 MeV). For the third fermion generation mu is the value of the dynamical techniquark mass (approximate to250 GeV). We discuss how this possibility can be implemented in a technicolor scenario, and how the mass of the intermediate generation is generated.

Quark clustering and chiral symmetry breaking in nuclear matter

Chiral symmetry breaking at finite baryon density is usually discussed in the context of quark matter, i.e. a system of deconfined quarks. Many systems like stable nuclei and neutron stars however have quarks confined within nucleons. In this paper we construct a Fermi sea of three-quark nucleon clusters and investigate the change of the quark condensate as a function of baryon density. We study the effect of quark clustering on the in-medium quark condensate and compare results with the traditional approach of modeling hadronic matter in terms of a Fermi sea of deconfined quarks.

BCS superconductivity in the van Hove scenario in s and d waves

The effect of including a van Hove singularity in the density of state of a renormalized BCS equation in s and d waves and its appropriateness in describing some properties of high-Tc cuprates in the weak-coupling region are studied in two space dimensions. The specific heat and knight shift as a function of temperature exhibit scaling below the critical temperature in d wave. We also study the jump in the specific heat at the critical temperature Tc in s and d waves, which can have values significantly higher than the standard BCS values and which increases with Tc, as experimentally observed in many d-wave high-Tc materials. The experimental results on the specific heat and knight shift of the Y-123 system are compared with the theoretical predictions.

De sitter relativity: a natural scenario for an evolving Lambda

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)