9 research outputs found

    WICC 2017 : XIX Workshop de Investigadores en Ciencias de la Computación

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    Actas del XIX Workshop de Investigadores en Ciencias de la Computación (WICC 2017), realizado en el Instituto Tecnológico de Buenos Aires (ITBA), el 27 y 28 de abril de 2017.Red de Universidades con Carreras en Informática (RedUNCI

    WICC 2016 : XVIII Workshop de Investigadores en Ciencias de la Computación

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    Actas del XVIII Workshop de Investigadores en Ciencias de la Computación (WICC 2016), realizado en la Universidad Nacional de Entre Ríos, el 14 y 15 de abril de 2016.Red de Universidades con Carreras en Informática (RedUNCI

    XX Workshop de Investigadores en Ciencias de la Computación - WICC 2018 : Libro de actas

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    Actas del XX Workshop de Investigadores en Ciencias de la Computación (WICC 2018), realizado en Facultad de Ciencias Exactas y Naturales y Agrimensura de la Universidad Nacional del Nordeste, los dìas 26 y 27 de abril de 2018.Red de Universidades con Carreras en Informática (RedUNCI

    XX Workshop de Investigadores en Ciencias de la Computación - WICC 2018 : Libro de actas

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    Actas del XX Workshop de Investigadores en Ciencias de la Computación (WICC 2018), realizado en Facultad de Ciencias Exactas y Naturales y Agrimensura de la Universidad Nacional del Nordeste, los dìas 26 y 27 de abril de 2018.Red de Universidades con Carreras en Informática (RedUNCI

    Bootstrap e modelos de Support Vector Machine - SVM

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    Orientador : Prof. Dr. Anselmo Chaves NetoTese (doutorado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Métodos Numéricos em Engenharia. Defesa: Curitiba, 28/03/2016Inclui referências : f. 106-110Área de concentração : Programação matemáticaResumo: A tese apresenta duas metodologias novas para a fase de ajuste de modelos de Máquinas de Vetores Suporte (Support Vector Machines - SVM) aplicados tanto em problemas de classificação de padrões, quanto em problemas de regressão (Support Vector Regression - SVR), e uma metodologia de obtenção de margens alternativa as já existentes para modelos SVR. Para as metodologias propostas, são apresentadas aplicações na medicina tais como: na classificação de grau da doença Ceratocone que atinge a córnea, na previsão do grau de astigmatismo com base nos exames clínicos. Apresenta, também, aplicação na climatologia, na previsão da temperatura e aplicação na parte hídrica quanto à previsão da evaporação de água em reservatórios. O primeiro método se baseia na criação de uma constante reguladora para as variáveis independentes dos modelos, levando em consideração o valor da correlação das mesmas com a variável dependente. Já o segundo método, utiliza a técnica computacionalmente intensiva de reamostragens Bootstrap para a fase de ajuste dos modelos SVM, liberando observações originais para a fase de teste. O Bootstrap é usado, ainda, na criação de novas margens flexíveis para os modelos SVR, com base no intervalo de confiança bootstrap-t, gerando uma forma alternativa de se obter as margens flexíveis. As soluções das modelagens foram obtidas pelo método Least Squares Support Vector Machine - LS-SVM, devido a sua menor complexidade matemática e computacional, em relação à solução dos modelos SVM. Em todas as aplicações, as metodologias desenvolvidas neste trabalho obtiveram resultados para a raiz do erro médio quadrático (RMSE) menores que para os modelos SVM convencionais, evidenciando assim a eficiência dos métodos desenvolvidos. Palavras-Chave: Bootstrap, Support Vector Machine, Classificação, Regressão.Abstract: The thesis presents two new methodologies for adjust phase for models based on Support Vector Machines (Support Vector Machines - SVM) applied both in pattern classification problems, as in regression problems (Support Vector Regression - SVR), and a methodology of obtaining alternative margins existing for SVR models. The paper presents applications in medicine: classification of Keratoconus disease degree that affects the cornea, in predicting the degree of astigmatism based on clinical examinations; weather: on the forecast of temperature and finally in with forecast of evaporation of water in reservoirs. The first method is based on the creation of a regulatory constant for the independent variables of the model, taking into account the value of their correlation with the dependent variable. The second method uses the Bootstrap resampling for the training phase of the SVM models, releasing the original samples for testing phase. The third is to use the Bootstrap method to create the new flexible margins for SVR models, based on the bootstrap-t confidence interval, generating an alternative way to obtain the flexible margins. The solutions of the moldings were obtained by the least squares method Support Vector Machine - LS-SVM due to its smaller mathematical and computational complexity compared to the solution of SVM models. In all applications, the methodologies developed in this thesis obtained results for mean square error (RMSE) lower than for conventional SVM models, thus demonstrating the effectiveness of the methods developed. Key-Words: Bootstrap, Support Vector Machine, Classification, Regression

    XXI Workshop de Investigadores en Ciencias de la Computación - WICC 2019: libro de actas

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    Trabajos presentados en el XXI Workshop de Investigadores en Ciencias de la Computación (WICC), celebrado en la provincia de San Juan los días 25 y 26 de abril 2019, organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y la Facultad de Ciencias Exactas, Físicas y Naturales de la Universidad Nacional de San Juan.Red de Universidades con Carreras en Informátic

    XXI Workshop de Investigadores en Ciencias de la Computación - WICC 2019: libro de actas

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    Trabajos presentados en el XXI Workshop de Investigadores en Ciencias de la Computación (WICC), celebrado en la provincia de San Juan los días 25 y 26 de abril 2019, organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y la Facultad de Ciencias Exactas, Físicas y Naturales de la Universidad Nacional de San Juan.Red de Universidades con Carreras en Informátic

    Modelling a conversational agent (Botocrates) for promoting critical thinking and argumentation skills

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    Students in higher education institutions are often advised to think critically, yet without being guided to do so. The study investigated the use of a conversational agent (Botocrates) for supporting critical thinking and academic argumentation skills. The overarching research questions were: can a conversational agent support critical thinking and academic argumentation skills? If so, how? The study was carried out in two stages: modelling and evaluating Botocrates' prototype. The prototype was a Wizard-of-Oz system where a human plays Botocrates' role by following a set of instructions and knowledge-base to guide generation of responses. Both stages were conducted at the School of Education at the University of Leeds. In the first stage, the study analysed 13 logs of online seminars in order to define the tasks and dialogue strategies needed to be performed by Botocrates. The study identified two main tasks of Botocrates: providing answers to students' enquiries and engaging students in the argumentation process. Botocrates’ dialogue strategies and contents were built to achieve these two tasks. The novel theoretical framework of the ‘challenge to explain’ process and the notion of the ‘constructive expansion of exchange structure’ were produced during this stage and incorporated into Botocrates’ prototype. The aim of the ‘challenge to explain’ process is to engage users in repeated and constant cycles of reflective thinking processes. The ‘constructive expansion of exchange structure’ is the practical application of the ‘challenge to explain’ process. In the second stage, the study used the Wizard-of-Oz (WOZ) experiments and interviews to evaluate Botocrates’ prototype. 7 students participated in the evaluation stage and each participant was immediately interviewed after chatting with Botocrates. The analysis of the data gathered from the WOZ and interviews showed encouraging results in terms of students’ engagement in the process of argumentation. As a result of the role of ‘critic’ played by Botocrates during the interactions, users actively and positively adopted the roles of explainer, clarifier, and evaluator. However, the results also showed negative experiences that occurred to users during the interaction. Improving Botocrates’ performance and training users could decrease users’ unsuccessful and negative experiences. The study identified the critical success and failure factors related to achieving the tasks of Botocrates

    XXIII Edición del Workshop de Investigadores en Ciencias de la Computación : Libro de actas

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    Compilación de las ponencias presentadas en el XXIII Workshop de Investigadores en Ciencias de la Computación (WICC), llevado a cabo en Chilecito (La Rioja) en abril de 2021.Red de Universidades con Carreras en Informátic
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