9 resultados para Meaning-Text unification grammar

em Repositório Científico do Instituto Politécnico de Lisboa - Portugal


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In the present study we focus on the interaction between the acquisition of new words and text organisation. In the acquisition of new words we emphasise the acquisition of paradigmatic relations such as hyponymy, meronymy and semantic sets. We work with a group of girls attending a private school for adolescents in serious difficulties. The subjects are from disadvantaged families. Their writing skills were very poor. When asked to describe a garden, they write a short text of a single paragraph, the lexical items were generic, there were no adjectives, and all of them use mainly existential verbs. The intervention plan assumed that subjects must to be exposed to new words, working out its meaning. In presence of referents subjects were taught new words making explicit the intended relation of the new term to a term already known. In the classroom subjects were asked to write all the words they knew drawing the relationships among them. They talk about the words specifying the relation making explicit pragmatic directions like is a kind of, is a part of or are all x. After that subjects were exposed to the task of choosing perspective. The work presented in this paper accounts for significant differences in the text of the subjects before and after the intervention. While working new words subjects were organising their lexicon and learning to present a whole entity in perspective.

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The idea of grand unification in a minimal supersymmetric SU(5) x SU(5) framework is revisited. It is shown that the unification of gauge couplings into a unique coupling constant can be achieved at a high-energy scale compatible with proton decay constraints. This requires the addition of minimal particle content at intermediate energy scales. In particular, the introduction of the SU(2)(L) triplets belonging to the (15, 1)+((15) over bar, 1) representations, as well as of the scalar triplet Sigma(3) and octet Sigma(8) in the (24, 1) representation, turns out to be crucial for unification. The masses of these intermediate particles can vary over a wide range, and even lie in the TeV region. In contrast, the exotic vector-like fermions must be heavy enough and have masses above 10(10) GeV. We also show that, if the SU(5) x SU(5) theory is embedded into a heterotic string scenario, it is not possible to achieve gauge coupling unification with gravity at the perturbative string scale.

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Projeto de Intervenção apresentado à Escola Superior de Educação de Lisboa para a obtenção de grau de Mestre em Didática da Língua Portuguesa no 1º e 2º CEB

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Projeto de Intervenção apresentado à Escola Superior de Educação de Lisboa para obtenção de grau de Mestre em Didática da Língua Portuguesa no 1.º e 2.º Ciclos do Ensino Básico

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Relatório apresentado à Escola Superior de Educação de Lisboa para obtenção do grau de mestre em Ensino do 1.º e 2.º Ciclos do Ensino Básico

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We look for minimal chiral sets of fermions beyond the standard model that are anomaly free and, simultaneously, vectorlike particles with respect to color SU(3) and electromagnetic U(1). We then study whether the addition of such particles to the standard model particle content allows for the unification of gauge couplings at a high energy scale, above 5.0 x 10(15) GeV so as to be safely consistent with proton decay bounds. The possibility to have unification at the string scale is also considered. Inspired in grand unified theories, we also search for minimal chiral fermion sets that belong to SU(5) multiplets, restricted to representations up to dimension 50. It is shown that, in various cases, it is possible to achieve gauge unification provided that some of the extra fermions decouple at relatively high intermediate scales.

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Relatório de Estágio apresentado à Escola Superior de Educação de Lisboa para obtenção do grau de mestre em Ensino dos 1.º e 2.º Ciclos do Ensino Básico

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Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Educação Matemática na Educação Pré-escolar e nos 1.º e 2.º ciclos do Ensino Básico

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Arguably, the most difficult task in text classification is to choose an appropriate set of features that allows machine learning algorithms to provide accurate classification. Most state-of-the-art techniques for this task involve careful feature engineering and a pre-processing stage, which may be too expensive in the emerging context of massive collections of electronic texts. In this paper, we propose efficient methods for text classification based on information-theoretic dissimilarity measures, which are used to define dissimilarity-based representations. These methods dispense with any feature design or engineering, by mapping texts into a feature space using universal dissimilarity measures; in this space, classical classifiers (e.g. nearest neighbor or support vector machines) can then be used. The reported experimental evaluation of the proposed methods, on sentiment polarity analysis and authorship attribution problems, reveals that it approximates, sometimes even outperforms previous state-of-the-art techniques, despite being much simpler, in the sense that they do not require any text pre-processing or feature engineering.