Orientadores: Celmar Guimarães da Silva, Luiz Camolesi Júnior / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Tecnologia / Made available in DSpace on 2018-08-20T16:53:09Z (GMT). No. of bitstreams: 1 Melo_MarivaldoFelipede_M.pdf: 9855716 bytes, checksum: 793ed5d070fcd3285d9dc52d700caecf (MD5) Previous issue date: 2012 / Resumo: Algoritmos de reordenação são importantes para analise de dados matriciais, pois encontram automaticamente permutações de linhas e colunas que agrupam valores semelhantes em uma matriz, visando facilitar a busca visual por padrões e tendências nos dados. Alem disso, esses algoritmos tendem a reduzir a sobrecarga cognitiva do usuário, tendo em vista que, diferentemente das abordagens anteriores a seriação, o usuário não precisa permutar manualmente linhas e colunas para encontrar padrões. Entre os algoritmos de reordenação de matrizes pesquisados, destaca-se o PQR-Sort, por sua natureza não-heuristica e baixa complexidade assintótica de tempo de execução. Com base nesse algoritmo, este trabalho objetiva produzir versões aprimoradas do PQR-Sort visando melhorar a qualidade das matrizes por ele reordenadas (medida por funções de avaliação). Como principais resultados, foram criados dois novos algoritmos, PQR-Sort with Sorted Restrictions e PQR-Sort + BC, cujos resultados são melhores que os do algoritmo PQR-Sort de acordo com funções de avaliação de caráter local e global, respectivamente. O trabalho apresenta ainda um estudo de caso sobre a aplicação dos algoritmos propostos a um conjunto de dados real / Abstract: Reordering algorithms are important in matrix data analysis, because they automatically find row and column permutations that group similar data in a table, in order to ease finding patterns and trends in the data. Furthermore, these algorithms tend to reduce the user's cognitive overload, since, unlike previous reordering approaches, users don't need to swap rows and columns manually in order to find patterns. Within the surveyed reordering algorithms, PQR-Sort stands out because of its nonheuristic nature and low asymptotic time complexity. Based on this algorithm, this work aims to produce enhanced versions of PQR-Sort in order to improve the quality of the reordered matrix (measured by evaluators). Among its main results is the creation of two new algorithms: PQRSort with sorted Restrictions and PQR-Sort + BC, which perform better than PQR-Sort according to local e global evaluators, respectively. This work also presents a study case about the proposed algorithms' application in a real dataset / Mestrado / Tecnologia e Inovação / Mestre em Tecnologia

Effect mapping is a method often used by companies in order to try to tie together the business goals with the users and their needs. The results of the effect mapping is often presented in long reports, with an additional effect map attached to it. Unfortunately, few clients tend to read these reports that they later are supposed to base future decisions on. This thesis aims to examine the efficiency in readers' perception of information, specifically the information from effect mapping. It evaluates if the understanding and perception, as well as the participation, could be improved by developing a digital web based version of the information. The objective of this study is to determine if a visualized web version of the effect mapping is more efficient than the original paper report version. The purpose is to help consulting firms improve the communication with their clients, that the clients will take part of and consume the information provided by the effect mappings that are delivered in a more efficient way. The process started out with workshops that were a foundation for a prototype. The prototype was developed based on the theoretical framework of this thesis, and created from a specific example of a traditional effect mapping report. The prototype was tested and evaluated before compared to, and evaluated with, the original paper report version of the effect mapping. The findings are that a web based, visualized presentation of the effect mapping is more efficient than the original paper report version. Not only did the participants of the study find the correct information in a shorter amount of time, but the user experience was also enhanced. The findings in this study are useful for firms that want to present results of effect mapping to customers who do not tend to spend time reading the full reports, but would rather get a quicker overview. This study can be used as a point of departure for future research, by testing it on other reports or firms.

This paper describes the design, implementation and evaluation of HyperSALmon, a Java™ open source prototype for visualizing service models in telecommunication networks. For efficient browsing and graphical monitoring of service models using SALmon, a service modeling language and a monitoring engine (Leijon et al., 2008), some kind of interactive GUI that implements a visualization of the service model is desired. This is what HyperSALmon is intended to do. The prototype has been designed in accordance with suggestions derived from a current research report of visualization techniques (Sehlstedt, 2008) appropriate for displaying service model data. In addition to these suggestions domain experts at Data Ductus Nord AB has expressed an urge for implementation of further features, some of their suggestions are deduced from research documents (Leijon et al., 2008; Wallin and Leijon, 2007, 2006), while others have been stated orally in direct relation to the prototype implementation work. The main visualization proposal is to use tree structures. Thus, both traditional tree structures and hyperbolic tree structures have been utilized, where the main navigation is set to occur in the hyperbolic tree view. In order to contribute further to this report I provide a discussion addressing problems related to the context of implementing a prototype for service model visualization using open source frameworks that meets the requirements set by the service model network architecture, the domain experts and the suggestions in the research report (Sehlstedt, 2008,page 51-52). Finally, I will present drawn conclusions of the attempted prototype implementation, illustrating potential strengths and weaknesses and consequently introduce suggestions for possible improvement and further development.

Zoonotic diseases are diseases that are transmitted from animals or vectors to humans and vice versa. The public together with veterinarian authorities should readily access disease information as it is vital in rapidly controlling resultant zoonotic outbreak threats through improved awareness. Currently, the reporting of disease information in South Africa is predominantly limited to traditional methods of Information Communication Technologies (ICTs) like faxes, monthly newspaper reports, radios, phones and televisions. Although these are effective ways of communication, their disadvantage is that the information that most of them offer can only be accessed at specific times during a crisis. New technologies like the internet have become the most efficient way of distributing information in near-real-time. Many developed countries have used web-based reporting platforms to deliver timely information through temporal and geographic visualisation techniques. There has been an attempt in the use of web-based reporting in South Africa but most of these sites are characterised by heavy text which makes them time consuming to use or maintain. As a result most sites have not been updated or have ceased to exist because of the work load involved. The success of web reporting mechanisms in developed countries offers evidence that web-based reporting systems when appropriately visualised can improve the easy understanding of information and efficiency in the analysis of that data. In this thesis, a web-based reporting prototype was proposed after gathering information from different sources: literature related to disease reporting and the visualisation of infectious diseases; the exploration of the currently deployed web systems; and the investigation of user requirements from relevant parties. The proposed prototype system was then developed using Adobe Flash tools, Java and MySQL languages. A focus group then reviewed the developed system to ascertain that the relevant requirements had been incorporated and to obtain additional ideas about the system. This led to the proposal of a new prototype system that can be used by the authorities concerned as a plan to develop a fully functional disease reporting system for South Africa.

Web Usage Mining (WUM) can be used to determine whether the information architecture of a web site is structured correctly. Existing WUM tools however, do not indicate which web usage mining algorithms are used or provide effective graphical visualisations of the results obtained. WUM techniques can be used to determine typical navigation patterns of the users of organisational web sites. An organisational web site can be described as a site which has a high level of content. The Computer Science & Information Systems (CS&IS) web site at the Nelson Mandela Metropolitan University (NMMU) is an example of such a web site. The process of combining WUM and information visualisation techniques in order to discover useful information about web usage patterns is called visual web mining. The goal of this research is to discuss the development of a WUM model and a prototype, called WebPatterns, which allows the user to effectively visualise web usage patterns of an organisational web site. This will facilitate determining whether the information architecture of the CS&IS web site is structured correctly. The WUM algorithms used in WebPatterns are association rule mining and sequence analysis. The purpose of association rule mining is to discover relationships between different web pages within a web site. Sequence analysis is used to determine the longest time ordered paths that satisfy a user specified minimum frequency. A radial tree layout is used in WebPatterns to visualise the static structure of the organisational web site. The structure of the web site is laid out radially, with the home page in the middle and other pages positioned in circles at various levels around it. Colour and other visual cues are used to show the results of the WUM algorithms. User testing was used to determine the effectiveness and usefulness of WebPatterns for visualising web usage patterns. The results of the user testing clearly show that the participants were highly satisfied with the visual design and information provided by WebPatterns. All the participants also indicated that they would like to use WebPatterns in the future. Analysis of the web usage patterns presented by WebPatterns was used to determine that the information architecture of the CS&IS web site can be restructured to better facilitate information retrieval. Changes to the CS&IS web site web were suggested, included placing embedded hyperlinks on the home page to the frequently accessed sections of the web site.

La visualisation d'information est une discipline récente en pleine expansion et qui a pour objet l'étude des méthodes de représentation visuelle de données abstraites, c'est-à-dire non géolocalisées. La sémiotique est quant à elle une discipline beaucoup plus ancienne (fin du XIXième siècle) qui s'intéresse aux divers systèmes de signes nécessaires aux processusde communication. A ce jour, peu de travaux ont été réalisés pour mettre en parallèle ces deux disciplines. C'est pourquoi le premier chapitre de cette thèse est dédié à l'étude de la visualisation d'information selon les paradigmes élaborés par son ainée tout au long du XXième siècle. Nous montrons en particulier comment l'un des modèles les plus aboutis de validation de visualisations (modèle imbriqué de Tamara Munzner) correspond au processus d'étude sémiotique d'énoncés. Le second chapitre est consacré à la visualisation de graphe, outil de modélisation puissant de divers ensembles de données abstraites. Nous proposons d'une part une application permettant de visualiser et de naviguer à travers les pages Internet retournées par un moteur de recherche et d'autre part un algorithme de visualisation de hiérarchies dynamiques sous forme de "cartes géographiques". Enfin, nous évoquons dans le troisième chapitre un autre outil de modélisation de donnéesabstraites : les hypergraphes. Nous proposons des résultats théoriques concernant leur représentation et donnons une ébauche de solution permettant de les visualiser. / Information visualization aims at designing visual representations of abstract data, furthermore relying on interaction as a mean to discover knowledge. The first part of this thesis challenges Information Visualization by drawing a parallel with semiotics, a 19th century research field focusing on systems of signs required for communication. We develop a point of view on Information Visualization based on the paradigms developed by semioticians during the 20th century. In particular, we show how the visualization validation model proposed by Tamara Munzner is related to the process used by semioticians for utterance analysis. The second part of the thesis focuses on graph visualization and describes two techniques and system prototypes targeting specific application domains. The first one is an interactive technique to visualize and navigate through Web search results. The second one is an algorithm for the visualization of dynamic hierarchies exploiting the analogy with “geographical maps”. Finally, the third chapter is devoted to another model used to structure abstract data : hypergraphs. We propose theoretical results on hypergraph drawing and a preliminary technique to visualize hypergraphs.

O processo automático de classificação de dados em geral, e em particular de classificação de imagens, é uma tarefa computacionalmente intensiva e variável em termos de precisão, sendo consideravelmente dependente da configuração do classificador e da representação dos dados utilizada. Muitos dos fatores que afetam uma adequada aplicação dos métodos de classificação ou categorização para imagens apontam para a necessidade de uma maior interferência do usuário no processo. Para isso são necessárias mais ferramentas de apoio às várias etapas do processo de classificação, tais como, mas não limitadas, a extração de características, a parametrização dos algoritmos de classificação e a escolha de instâncias de treinamento adequadas. Este doutorado apresenta uma metodologia para Classificação Visual de Imagens, baseada na inserção do usuário no processo de classificação automática através do uso de técnicas de visualização. A ideia é permitir que o usuário participe de todos os passos da classificação de determinada coleção, realizando ajustes e consequentemente melhorando os resultados de acordo com suas necessidades. Um estudo de diversas técnicas de visualização candidatas para a tarefa é apresentado, com destaque para as árvores de similaridade, sendo apresentadas melhorias do algoritmo de construção em termos de escalabilidade visual e de tempo de processamento. Adicionalmente, uma metodologia de redução de dimensionalidade visual semi-supervisionada é apresentada para apoiar, pela utilização de ferramentas visuais, a criação de espaços reduzidos que melhorem as características de segregação do conjunto original de características. A principal contribuição do trabalho é um sistema de classificação visual incremental que incorpora todos os passos da metodologia proposta, oferecendo ferramentas interativas e visuais que permitem a interferência do usuário na classificação de coleções incrementais com configuração de classes variável. Isso possibilita a utilização do conhecimento do ser humano na construção de classificadores que se adequem a diferentes necessidades dos usuários em diferentes cenários, produzindo resultados satisfatórios para coleções de dados diversas. O foco desta tese é em categorização de coleções de imagens, com exemplos também para conjuntos de dados textuais / Automatic data classification in general, and image classification in particular, are computationally intensive tasks with variable results concerning precision, being considerably dependent on the classifier´s configuration and data representation. Many of the factors that affect an adequate application of classification or categorization methods for images point to the need for more user interference in the process. To accomplish that, it is necessary to develop a larger set of supporting tools for the various stages of the classification set up, such as, but not limited to, feature extraction, parametrization of the classification algorithm and selection of adequate training instances. This doctoral Thesis presents a Visual Image Classification methodology based on the user´s insertion in the classification process through the use of visualization techniques. The idea is to allow the user to participate in all classification steps, adjusting several stages and consequently improving the results according to his or her needs. A study on several candidate visualization techniques is presented, with emphasis on similarity trees, and improvements of the tree construction algorithm, both in visual and time scalability, are shown. Additionally, a visual semi-supervised dimensionality reduction methodology was developed to support, through the use of visual tools, the creation of reduced spaces that improve segregation of the original feature space. The main contribution of this work is an incremental visual classification system incorporating all the steps of the proposed methodology, and providing interactive and visual tools that permit user controlled classification of an incremental collection with evolving class configuration. It allows the use of the human knowledge on the construction of classifiers that adapt to different user needs in different scenarios, producing satisfactory results for several data collections. The focus of this Thesis is image data sets, with examples also in classification of textual collections

Este trabalho apresenta o Super Spider: um sistema de exploração visual baseado no Spider Cursor, que abrange várias técnicas interativas da área de Visualização Computacional e conta com novos recursos de auxílio à investigação visual, além de ser uma ferramenta portável e flexível. / This work presents the Super Spider: a visual exploration system, based on Spider Cursor, that embraces many interactive techniques of Computer Visualization area and take into account innovative techniques to aid visual investigation, besides consisting of a portable and flexible tool.

O crescente uso de ambientes virtuais de aprendizagem faz com que os professores e desenvolvedores precisem avaliar qual o melhor formato de visualização a ser utilizado. Infográfico é tipo de visualização de informação que vem ganhando popularidade no contexto educacional. Ele utiliza figuras, gráficos e curtas explicações textuais associados à elementos de design, para transformar informações complexas em visualizações simples. No entanto, poucos trabalhos empíricos investigam a interferência do formato infográfico no processo de aprendizagem e consideram a influência dos estados afetivos (em particular a satisfação) e a preferência (i.e. estilo de aprendizagem) do aluno na sua capacidade de reter informação quando o material apresentado é o infográfico. Esse trabalho de mestrado tem como objetivo investigar os benefícios educacionais do uso de infográficos como material de aprendizagem comparando-os com materiais tradicionais, texto puro e gráfico+texto. Também visa analisar a influência de outras variáveis experimentais no processo de aprendizagem como complexidade do infográfico, satisfação e estilo de aprendizagem. Para isso, foi executado um experimento com 74 alunos de graduação distribuídos entre três formatos de materiais de aprendizagem (i.e. infográficos, gráficos+texto e texto puro) em uma sessão de aprendizagem individual suportada por computador. Os sujeitos foram avaliados quanto à aprendizagem imediata, retenção e perda de conhecimento, satisfação, estilos de aprendizagem e tempo. Os resultados obtidos sugerem que os infográficos são tão bons para a aprendizagem e retenção de conhecimento quanto os materiais tradicionais. Não foram encontradas evidências de que os estilos de aprendizagem visual ou verbal têm impacto na aprendizagem ou na satisfação dos alunos. Além disso, foram encontrados indícios de que satisfações positivas podem resultar em uma maior retenção de conhecimento. Para analisar a variável complexidade, foi proposto um framework para classificação dos infográficos. Pode-se concluir que, de fato, infográficos classificados como de baixa complexidade proporcionam maior aprendizagem. No entanto, o aprendizado por meio dos infográficos de complexidade alta não foi significativamente menor. É possível atribuir essa queda não significativa à natureza explicativa dos infográficos, capaz de estabilizar o aprendizado do aluno a partir de um determinado nível de complexidade, mesmo que a complexidade aumente. / The increasing use of virtual learning environments lead teachers and developers to assess what is the best visualization format to use. Infographic is an information visualization format that has gained the educational context. It uses figures, graphs, and short textual explanations associated with design elements, to transform complex information into simple display. However, few empirical studies investigate the interference of the infographic format in the learning process and consider the influence of affective states (in particular enjoyment) and preference (i.e., learning styles) in students information retention when using infographics. This masters dissertation aims at investigating the educational benefits of using infographics as learning material and comparing them to traditional materials, pure text and graphic+text. In addition, it aims at analysing the influence of other experimental variables such as infographics complexity, students satisfaction and learning style. For this, an experiment was carried out with 74 undergraduate students distributed among three formats of learning materials (i.e., infographics, graphics+text and pure text) in a computer-supported individual learning session. Subjects were evaluated about immediate learning, retention and loss of knowledge, satisfaction, learning styles and time. The results suggest that infographics are as good for learning and retention as traditional materials. There is no evidence that visual or verbal learning styles impact on student learning or enjoyment. In addition, evidence has been found that positive satisfactions may result in greater retention of information. To analyze the infographics complexity, a framework was proposed to classify infographics. It can be concluded that, in fact, infographics classified as low complexity provide greater results for learning. However, learning through infographics of high complexity was not significantly smaller. It is possible to assign this non-significant dacay to the infographics explanatory nature, capable of steading the students learning from a certain level of complexity.

Há várias décadas, pesquisadores em ciências sociais buscam formas gráficas para expressar as relações humanas na sociedade. O advento do computador e, mais recentemente, da internet, possibilitou o surgimento de um campo que tem despertado a atenção de estudiosos das áreas de visualização de informação e de ciências sociais, o da visualização de redes sociais. Esse campo tem o potencial de revelar e explorar padrões que podem beneficiar um número muito grande de aplicações e indivíduos em áreas tais como comércio, segurança em geral, redes de conhecimento e pesquisa de mercado. Grande parte dos algoritmos de visualização de redes sociais são baseados em grafos, destacando relacionamentos entre indivíduos e grupos de indivíduos, mas dando pouca atenção aos seus demais atributos. Assim, este trabalho apresenta um conjunto de soluções para representar e explorar visualmente redes sociais levando em consideração tais atributos. A primeira solução faz uso de redes heterogêneas, onde tanto indivíduos quanto comunidades são representados no grafo; a segunda solução utiliza técnicas de visualização baseadas em projeção multidimensional, que promovem o posicionamento dos dados no plano de acordo com algum critério de similaridade baseado em atributo; e a última solução coordena múltiplas visões para focar rapidamente em regiões de interesse. Os resultados indicam que as soluções proveem um poder de representação e identificação de conceitos não facilmente detectados por formas convencionais de visualização e exploração de grafos, com indícios fornecidos através dos estudos de caso e da realização de avaliações com usuários. Este trabalho fornece um estudo das áreas de visualização em grafos para a análise de redes sociais bem como uma implementação das soluções de integração da visualização em redes com as projeções multidimensionais / For decades, social sciences researchers have searched for graphical forms to express human social relationships. The development of computer science and more recently of the Internet has given rise to a new field of research for visualization and social sciences professionals, that of social network visualization. This field can potentially offer new opportunities in reveal new patterns that can benefit a large number of applications and individuals in fields such as commerce, security, knowledge networks and marketing. A large part of social network visualization algorithms and systems relies on graph representations, highlighting relationships amongst individuals and groups of individuals, but mostly neglecting the other available attributes of individuals. Thus, this work presents a set of tools to represent and explore social networks visually, taking into consideration the attributes of the nodes. The first technique employs heterogeneous networks, where both individuals and communities are represented in the graph; the second solution uses visualization techniques based on multidimensional projection, which promote the placement of data in the plane according to some similarity criterion based on attribute; still another proposed technique coordinates multiple views in order to speed up focus in regions of interest in the data sets. The results indicate that the solutions promote high degree of representation power and that concept identification not easily obtained via other methods is possible; the evidence comes from case studies as well as a user evaluation. This work includes a study in the area of graph visualization for social network analysis as well as a system implementing the proposed solutions, that integrate network visualization and multidimensional projections to extract patterns from social networks