La publication scientifique dans les revues spécialisées et les actes de conférences permet de communiquer les progrès en sciences. Les comités de rédaction et de programme sous-jacents représentent la clé de voûte du processus d'évaluation. Avec le développement des revues et le nombre croissant de conférences scientifiques organisées chaque année, rechercher des experts pour participer à ces comités est une activité chronophage mais critique. Cette thèse se focalise sur la tâche de suggestion de membres de comité de programme (CP) pour des conférences scientifiques. Elle comporte trois volets. Premièrement, nous proposons une modélisation basée sur un graphe hétérogène pondéré de l'expertise scientifique multifacette des chercheurs. Deuxièmement, nous définissons des indicateurs scientométriques pour quantifier les critères impliqués dans la constitution de CP. Troisièmement, nous concevons une approche de suggestion de membres de CP pour une conférence donnée, en combinant les résultats des indicateurs scientométriques susmentionnés. Notre approche est expérimentée pour une des conférences de premier plan de notre communauté de recherche : SIGIR, en considérant ses éditions de 1971 à 2015, ainsi que les conférences proches thématiquement. / Academic publishing in specialized journals and conference proceedings is the main way to communicate progress in science. The underlying editorial and program committees represent the cornerstone of the evaluation process. With the development of journals and the increasing number of scientific conferences held annually, searching for experts who would serve in these committees is a time-consuming and yet critical activity. This PhD thesis focuses on the task of suggesting program committee (PC) members for scientific conferences. It is organized into three parts. First, we propose a modelling of the multifaceted scientific expertise of researchers based on a weighted heterogeneous graph. Second, we define scientometric indicators to quantify the criteria involved in the composition of CPs. Third, we design a CP member suggestion approach for a given conference, combining the results of the aforementioned scientometric indicators. Our approach is experimented in the context of leading conferences of our research community: SIGIR, considering its editions from 1971 to 2015, and topically close conferences.

Os fóruns de discussões apresentam-se com umas das ferramentas de interação utilizadas nos ambientes virtuais de aprendizagem (AVAs). Esta pesquisa tem como objetivo propor um sistema computacional para recomendação de Objeto de Aprendizagem (OA), levando em consideração as postagens feitas de dentro dos fóruns de um Ambiente Virtual de Aprendizagem (AVA). A metodologia utilizada foi a pesquisa qualitativa, dos tipos descritiva e explicativa. Esse sistema identifica as palavras-chave nos fóruns de um AVA; usam as palavras-chave como indícios dos interesses dos usuários; classifica (atributos pesos) as palavras mais relevantes (Hot Topics); submete a um mecanismo de busca (repositório), neste trabalho foram usados os motores de busca, para fins de teste e oferece os resultados da busca aos usuários. As contribuições deste sistema para os sujeitos participantes desta pesquisa são: recomendação automática de OA para os alunos e professores; aplicação de mineração de dados para sistema gestão educacional; técnica de mineração de textos, utilizando algoritmo TF*PDF (Term Frequency * Proportional Document Frequency) e integração do AVA com repositório digital. Para validar o sistema de recomendação de OA em um AVA foi desenvolvido protótipo do sistema com uma amostra, contendo vinte e cinco alunos e cinco professores de duas turmas das disciplinas de Modelagem de Banco de Dados e Interface de Usuários e Sistemas Computacionais do curso de Engenharia de Computação da Universidade Estadual do Maranhão. O estudo realizado sobre o tema, e relatado nessa tese, tem como foco a recomendação de OA nos fóruns de um AVA. A avaliação e validação realizadas, através de protótipo do sistema com professores e alunos evidenciaram que o sistema de recomendação de Web Services (RECOAWS) proposto atende às expectativas e pode apoiar professores e alunos, nas suas atividades pedagógicas, dentro dos fóruns. / Discussion forums get present with one of interaction tools used in virtual learning environments (VLEs). This research aims to propose a computational system for Learning Object recommendation (LO), taking into account the posts made from within the forums of a Virtual Learning Environment (VLE). The methodology used was a qualitative study of descriptive and explanatory types. This system identifies the keywords in the forums of a VLE; It uses the keywords as evidence of the interests of users; ranks (attributes weights) the most relevant words (Hot Topics); It submits to a search engine (repository), this work were used search engines for testing purposes and provides the search results to users. The contributions of this system to the participants in this study are: automatic recommendation of LO for students and teachers; data mining application to educational management system; text mining techniques, using TF * PDF algorithm (Term Frequency * Proportional Document Frequency) and integration of the VLE with digital repository. To validate the LO recommendation system in a VLE was developed prototype system with a sample, with twenty-five students and five teachers from two classes of database modeling disciplines and User Interface and Computational Systems of Engineering course Computing of the State University of Maranhão. The study on the subject, and reported in this thesis is focused on LO recommendation in the forums of a VLE. The evaluation and validation performed by the prototype system with teachers and students showed that the Web Services recommendation system (RecoaWS) proposed meets expectations and can support teachers and students in their educational activities within the forums.

A busca de informações em bases de dados de instituições que possuem grande volume de dados necessita cada vez mais de processos mais eficientes para realização dessa tarefa. Problemas de grafia, idioma, sinonímia, abreviação de termos e a falta de padronização dos termos, tanto nos argumentos de busca, quanto na indexação dos documentos, interferem diretamente nos resultados. Diante disso, este estudo teve como objetivo avaliar o impacto da adição de vocabulários estruturados da área de Ciências da Saúde no Currículo Lattes, na recuperação de perfis similares de pesquisadores das áreas de Ciências Biológicas e Ciências da Saúde, utilizando técnicas de mineração de dados, expansão de consultas, modelos vetoriais de consultas e utilização de algoritmo de trigramas. Foram realizados cruzamentos de informações entre as palavras-chaves de artigos publicados registrados no Currículo Lattes e as informações contidas no Medical Subject Headings (MeSH) e nos Descritores em Ciências da Saúde (DeCS), bem como comparações entre os resultados das consultas, utilizando as palavras-chaves originais e adicionando-lhes os termos resultantes do processo de expansão de consultas. Os resultados mostram que a metodologia adotada neste estudo pode incrementar qualitativamente o universo de perfis recuperados, podendo dessa forma contribuir para a melhoria dos Sistemas de Informações do Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPq. / Information retrieval in large databases need increasingly more efficient ways for accomplishing this task. There are many problems, like spelling, language, synonym, acronyms, lack of standardization of terms, both in the search arguments, as in the indexing of documents. They directly interfere in the results. Thus, this study aimed to evaluate the impact of the addition of structured vocabularies of Health Sciences area in Lattes Database, in the recovery of similar profiles of researchers that work in Biological Sciences and Health Sciences, using Query Expansion, Data Mining procedures, Vector Models and Trigram Phrase Matching algorithm. Crosschecking keywords of articles registered in Lattes Database and Medical Subject Headings (MeSH) and Health Sciences Descriptors (DeCS) terms, as well as comparisons between the results of queries using the original keywords and adding them to query expansion terms. The results show that the methodology used in this study can qualitatively increase the set of recovered profiles, contributing to the improvement of CNPq Information Systems.

A presente tese versa sobre a construção de um Sistema de Recomendação (SR), denominado RecETC (Recomendador do ETC), para auxiliar no processo de Escrita Coletiva Digital (ECD) no Editor de Texto Coletivo (ETC). O RecETC tem como propósito a recomendação de materiais nos formatos de texto, imagens e vídeos, acerca do assunto que está sendo tratado na produção textual coletiva. Para a sua construção, utilizou-se da metodologia de estudo de caso através da abordagem qualitativa e quantitativa. Para isso, esta pesquisa foi desenvolvida em seis etapas, a saber: 1) Estudo teórico sobre as temáticas de Sistemas de Recomendação e Escrita Coletiva Digital, visando aprofundar o conhecimento nas respectivas áreas e identificar trabalhos correlatos. 2) Construção de Objetos de Aprendizagem produzidos como material de apoio para os cursos de extensão. 3) Desenvolvimento da primeira versão do RecETC. 4) Aplicação da primeira versão através de um curso piloto. 5) Desenvolvimento da segunda versão do RecETC 6) Aplicação da segunda versão em curso de extensão. Os dados foram coletados por meio de questionários e analisados tendo como base a metodologia de Análise de Conteúdo, o que possibilitou a definição de três categorias: Categoria I - O ETC como ambiente de Escrita Coletiva Digital, Categoria II - Requisitos técnicos do RecETC e Categoria III - Requisitos pedagógicos do RecETC. A partir do estudo do referencial teórico, do desenvolvimento e da análise das aplicações do RecETC por meio das categorias definidas, foi possível mapear os requisitos necessários para a sua construção e responder ao problema de pesquisa. Esses foram classificados em técnicos e/ou pedagógicos visando enfatizar os aspectos de funcionamento e as contribuições educacionais do RecETC para a ECD. Além disso, foi elaborado um plano de ação para auxiliar professores e alunos na ECD com o apoio do RecETC. Por fim, os resultados indicam que o desenvolvimento do RecETC atende ao propósito desse estudo e os requisitos identificados podem servir de referência para a construção de outros SR voltados para a ECD. / The present thesis deals with the construction of a Recommendation System (SR), called RecETC (ETC Recommender), to assist in the Digital Collective Writing (ECD) process in the Collective Text Editor (ETC). RecETC purpose is to recommend materials in text, image and video formats about the subject being treated in collective textual production. For its construction, it was used the methodology of case study through the qualitative and quantitative approach. For this, this research was developed in six stages, namely: 1) Theoretical study on the topics of Recommendation Systems and Digital Collective Writing, aiming to deepen the knowledge in the respective areas and to identify related works. 2) Construction of Learning Objects produced as support material for extension courses. 3) Development of the first version of RecETC. 4) Application of the first version through a pilot course. 5) Development of the second version of RecETC 6) Application of the second version in the course of extension. The data were collected through questionnaires and analyzed based on the Content Analysis methodology, which enabled the definition of three categories: Category I - ETC as a Digital Collective Writing environment, Category II - Technical requirements of RecETC and Category III - Pedagogical requirements of RecETC. From the study of the theoretical reference, development and analysis of RecETC applications through the defined categories, it was possible to map the necessary requirements for its construction and to respond to the research problem. These were classified as technical and / or pedagogical in order to emphasize the functional aspects and educational contributions of RecETC to ECD. In addition, a plan of action was developed to assist teachers and students in ECD with the support of RecETC. Finally, the results indicate that the development of RecETC fulfills the purpose of this study and the requirements identified can serve as a reference for the construction of other SRs focused on ECD.

The main aim of this diploma thesis is to find the inspiration for creating testing standards in the Czech Republic. The thesis is divided into two parts theoretical and practical. The theoretical part deals with the current form of Czech testing standards and also with testing standards which were created in other European countries. Pupils from these countries are already tested across the board. In the practical part I analyze the Austrian testing standards which were used as an inspiration for development of Czech testing standards. Then I sum up the agreements and on the other hand the differences between Czech and Austrian testing standards. Finally, the practical part is complemented with the author´s recommendation for development of Czech testing standards.

abstract: The rapid urban expansion has greatly extended the physical boundary of our living area, along with a large number of POIs (points of interest) being developed. A POI is a specific location (e.g., hotel, restaurant, theater, mall) that a user may find useful or interesting. When exploring the city and neighborhood, the increasing number of POIs could enrich people's daily life, providing them with more choices of life experience than before, while at the same time also brings the problem of "curse of choices", resulting in the difficulty for a user to make a satisfied decision on "where to go" in an efficient way. Personalized POI recommendation is a task proposed on purpose of helping users filter out uninteresting POIs and reduce time in decision making, which could also benefit virtual marketing. Developing POI recommender systems requires observation of human mobility w.r.t. real-world POIs, which is infeasible with traditional mobile data. However, the recent development of location-based social networks (LBSNs) provides such observation. Typical location-based social networking sites allow users to "check in" at POIs with smartphones, leave tips and share that experience with their online friends. The increasing number of LBSN users has generated large amounts of LBSN data, providing an unprecedented opportunity to study human mobility for personalized POI recommendation in spatial, temporal, social, and content aspects. Different from recommender systems in other categories, e.g., movie recommendation in NetFlix, friend recommendation in dating websites, item recommendation in online shopping sites, personalized POI recommendation on LBSNs has its unique challenges due to the stochastic property of human mobility and the mobile behavior indications provided by LBSN information layout. The strong correlations between geographical POI information and other LBSN information result in three major human mobile properties, i.e., geo-social correlations, geo-temporal patterns, and geo-content indications, which are neither observed in other recommender systems, nor exploited in current POI recommendation. In this dissertation, we investigate these properties on LBSNs, and propose personalized POI recommendation models accordingly. The performance evaluated on real-world LBSN datasets validates the power of these properties in capturing user mobility, and demonstrates the ability of our models for personalized POI recommendation. / Dissertation/Thesis / Doctoral Dissertation Computer Science 2014

abstract: Buildings consume nearly 50% of the total energy in the United States, which drives the need to develop high-fidelity models for building energy systems. Extensive methods and techniques have been developed, studied, and applied to building energy simulation and forecasting, while most of work have focused on developing dedicated modeling approach for generic buildings. In this study, an integrated computationally efficient and high-fidelity building energy modeling framework is proposed, with the concentration on developing a generalized modeling approach for various types of buildings. First, a number of data-driven simulation models are reviewed and assessed on various types of computationally expensive simulation problems. Motivated by the conclusion that no model outperforms others if amortized over diverse problems, a meta-learning based recommendation system for data-driven simulation modeling is proposed. To test the feasibility of the proposed framework on the building energy system, an extended application of the recommendation system for short-term building energy forecasting is deployed on various buildings. Finally, Kalman filter-based data fusion technique is incorporated into the building recommendation system for on-line energy forecasting. Data fusion enables model calibration to update the state estimation in real-time, which filters out the noise and renders more accurate energy forecast. The framework is composed of two modules: off-line model recommendation module and on-line model calibration module. Specifically, the off-line model recommendation module includes 6 widely used data-driven simulation models, which are ranked by meta-learning recommendation system for off-line energy modeling on a given building scenario. Only a selective set of building physical and operational characteristic features is needed to complete the recommendation task. The on-line calibration module effectively addresses system uncertainties, where data fusion on off-line model is applied based on system identification and Kalman filtering methods. The developed data-driven modeling framework is validated on various genres of buildings, and the experimental results demonstrate desired performance on building energy forecasting in terms of accuracy and computational efficiency. The framework could be easily implemented into building energy model predictive control (MPC), demand response (DR) analysis and real-time operation decision support systems. / Dissertation/Thesis / Doctoral Dissertation Industrial Engineering 2016

Made available in DSpace on 2014-10-09T12:52:56Z (GMT). No. of bitstreams: 0 / Made available in DSpace on 2014-10-09T14:01:56Z (GMT). No. of bitstreams: 0 / Tese (Doutoramento) / IPEN/T / Instituto de Pesquisas Energeticas e Nucleares - IPEN-CNEN/SP

Made available in DSpace on 2015-05-14T12:36:50Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 3864094 bytes, checksum: 906f3f1835bb4926fa07880cfa6fc539 (MD5) Previous issue date: 2014-02-10 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The object-oriented software componentization and development in the eighties aroused interested on developers towards the opportunities and advantages of software reuse, creating this same reuse in several stages of development, for instance, documentation, specification and modeling, increasing the search of better business opportunities, whether for reducing development costs or obtain produtivity gains. The development of these ideas led to the formulation of Software Product Lines model, which represents a shift in focus from the standardized paradigm of software development. Within this new paradigm, organizations that before addressed a project by project development software approach must now focus their efforts on creating and maintaining a line of software products which will be the basis for the production of a collection of products belonging to a "family". According to Clemente (2002), like all technological change, such a project should involve an assessment of the current situation of the company, an articulation of the desired state and the development of a plan to achieve this state. In the specific case of software product lines for being a model that directly interferes with the way of working of the company, extratechnological factors must be taken into account: adaptability of people, the type of training needed and preparing the client for new ways of working. The aim of this work is the creation of an Ontological approach to selection of distributed teams technically qualified for the implementation of software modules in a project of LPS, referring to the technical teams of the framework recommendations. This approach aims to provide decision support for project managers who aim to identify a set of qualifying teams for each module of a software project, taking into account the technical requirements of modules and technical skills in teams. This recommendation technical team was established by Santos (2010), using a fuzzy logic approach, structured in four stages. The first stage aims to produce a model description (generate an artifact) responsible for representing the technical requirements expected to implement each software module. The second step aims to generate a model of description responsible for representing the technical skills of the candidate teams to implement software modules. The third stage aims to define policies that will be responsible for selecting the qualified and/or able to implement software modules teams. Finally, the fourth step aims to cross the information obtained in previous steps and make the selection of the teams qualified for the implementation of the software modules. Thus, as a way out, for each software module recommendations are generated, which indicates team candidates who possess the most appropriate technical skills to implement software modules. Applying ontology to the problem of team recommendation is possible to represent the modules and their attributes in addition to expressing the relationships between the data collected, one can use axioms to deduce technically qualified teams. Team selection policies are offered with the intent of assisting the project manager in the selection of technically qualified teams for implementation of modules. In order to evaluate the ontological approach proposed, case studies are conducted, as well as a comparative study between the approach proposed in this paper and the fuzzy logic-based approach proposed by Santos (2010) / As iniciativas de componentização de software e de desenvolvimento de software orientado a objetos, na década de 80, despertaram o interesse de desenvolvedores para as oportunidades e vantagens da reutilização de código, gerando assim o reúso em diversas etapas do desenvolvimento, como por exemplo, documentação, especificação e modelagem, aumentando assim a busca por melhores oportunidades de negócio sejam para reduzir custos de desenvolvimento ou obter ganhos de produtividade. A evolução destas ideias levou a formulação do modelo de Linhas de Produtos de Software, que representa um deslocamento no foco do paradigma tradicional de desenvolvimento de software. Dentro desse novo paradigma, as organizações que antes abordavam o desenvolvimento de software projeto a projeto devem agora concentrar os seus esforços na criação e manutenção de uma linha de produtos de software a qual será a base para a produção de uma coleção de produtos pertencentes a uma família . Segundo Clemente (2002), como toda mudança tecnológica, esse tipo de projeto deve envolver uma avaliação da situação atual da empresa, uma articulação do estado desejado e a elaboração de um plano para atingir este estado. No caso específico de linhas de produtos de software, por se tratar de um modelo que interfere diretamente na maneira de trabalhar da empresa, fatores extratecnológicos devem ser considerados como: adaptabilidade das pessoas, o tipo de treinamento necessário e a preparação do cliente para a nova maneira de trabalhar. O objetivo desta dissertação é a criação de uma abordagem Ontológica para seleção de equipes distribruídas tecnicamente qualificadas para a implementação de módulos de software em um projeto de LPS, referente à recomendação técnica de equipes do framework de recomendações. Essa abordagem visa dar apoio à decisão aos gerentes de projetos que têm como objetivo identificar um conjunto de equipes qualificadas para cada módulo de software de um projeto, levando em consideração os requisitos técnicos dos módulos e as habilidades técnicas nas equipes. Essa recomendação técnica de equipes foi estabelecida em Santos (2010) utilizando uma abordagem de Lógica Fuzzy, estruturada em quatro etapas. A primeira etapa tem o objetivo de produzir um modelo de descrição (gerar um artefato) responsável por representar os requisitos técnicos esperados para implementar cada módulo de software. A segunda etapa tem o objetivo de gerar um modelo de descrição responsável por representar as habilidades técnicas das equipes candidatas a implementar os módulos de software. A terceira etapa tem o objetivo de definir políticas que serão responsáveis por selecionar as equipes habilitadas/aptas a implementar os módulos de software. E por fim, a quarta etapa tem como objetivo cruzar as informações obtidas em etapas anteriores e realizar a seleção das equipes habilitadas para a implementação dos módulos de software. Sendo assim, como saída, para cada módulo de software são geradas recomendações que indicam as equipes candidatas que possuam as habilidades técnicas mais adequadas para implementar os módulos de software. Aplicando ontologia ao problema de recomendação de equipes é possível representar os módulos e seus atributos além de expressar os relacionamentos entre os dados coletados, sendo possível utilizar axiomas para deduzir equipes tecnicamente qualificadas. A esse problema são propostas políticas de seleção de equipes que auxiliam o gerente de projetos no processo de seleção de equipes tecnicamente habilitadas para implementação dos módulos. Para avaliar a abordagem ontológica proposta são realizados estudos de casos, bem como um estudo comparativo entre a abordagem proposta nestre trabalho e a abordagem baseada em lógica fuzzy proposta em Santos (2010)

Os fóruns de discussões apresentam-se com umas das ferramentas de interação utilizadas nos ambientes virtuais de aprendizagem (AVAs). Esta pesquisa tem como objetivo propor um sistema computacional para recomendação de Objeto de Aprendizagem (OA), levando em consideração as postagens feitas de dentro dos fóruns de um Ambiente Virtual de Aprendizagem (AVA). A metodologia utilizada foi a pesquisa qualitativa, dos tipos descritiva e explicativa. Esse sistema identifica as palavras-chave nos fóruns de um AVA; usam as palavras-chave como indícios dos interesses dos usuários; classifica (atributos pesos) as palavras mais relevantes (Hot Topics); submete a um mecanismo de busca (repositório), neste trabalho foram usados os motores de busca, para fins de teste e oferece os resultados da busca aos usuários. As contribuições deste sistema para os sujeitos participantes desta pesquisa são: recomendação automática de OA para os alunos e professores; aplicação de mineração de dados para sistema gestão educacional; técnica de mineração de textos, utilizando algoritmo TF*PDF (Term Frequency * Proportional Document Frequency) e integração do AVA com repositório digital. Para validar o sistema de recomendação de OA em um AVA foi desenvolvido protótipo do sistema com uma amostra, contendo vinte e cinco alunos e cinco professores de duas turmas das disciplinas de Modelagem de Banco de Dados e Interface de Usuários e Sistemas Computacionais do curso de Engenharia de Computação da Universidade Estadual do Maranhão. O estudo realizado sobre o tema, e relatado nessa tese, tem como foco a recomendação de OA nos fóruns de um AVA. A avaliação e validação realizadas, através de protótipo do sistema com professores e alunos evidenciaram que o sistema de recomendação de Web Services (RECOAWS) proposto atende às expectativas e pode apoiar professores e alunos, nas suas atividades pedagógicas, dentro dos fóruns. / Discussion forums get present with one of interaction tools used in virtual learning environments (VLEs). This research aims to propose a computational system for Learning Object recommendation (LO), taking into account the posts made from within the forums of a Virtual Learning Environment (VLE). The methodology used was a qualitative study of descriptive and explanatory types. This system identifies the keywords in the forums of a VLE; It uses the keywords as evidence of the interests of users; ranks (attributes weights) the most relevant words (Hot Topics); It submits to a search engine (repository), this work were used search engines for testing purposes and provides the search results to users. The contributions of this system to the participants in this study are: automatic recommendation of LO for students and teachers; data mining application to educational management system; text mining techniques, using TF * PDF algorithm (Term Frequency * Proportional Document Frequency) and integration of the VLE with digital repository. To validate the LO recommendation system in a VLE was developed prototype system with a sample, with twenty-five students and five teachers from two classes of database modeling disciplines and User Interface and Computational Systems of Engineering course Computing of the State University of Maranhão. The study on the subject, and reported in this thesis is focused on LO recommendation in the forums of a VLE. The evaluation and validation performed by the prototype system with teachers and students showed that the Web Services recommendation system (RecoaWS) proposed meets expectations and can support teachers and students in their educational activities within the forums.