2013 XXVI Conference on Graphics, Patterns and Images 2013
DOI: 10.1109/sibgrapi.2013.22
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MIST: Multiscale Information and Summaries of Texts

Abstract: Fig. 1. MIST allows for the simultaneous visualization of individual documents as well as a summary of the document collection content, enabling multiscale exploration of subset of documents by content.Abstract-Combining distinct visual metaphors has been the mechanism adopted by several systems to enable the simultaneous visualization of multiple levels of information in a single layout. However, providing a meaningful layout while avoiding visual clutter is still a challenge. In this work we combine word clo… Show more

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Cited by 5 publications
(2 citation statements)
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“…O trabalho recentemente proposto por (PAGLIOSA et al, 2013) denominado Informação Multiescala e Sumarização de Texto (MIST) faz junção de duas abordagens, a word cloud e a rigid-body (Box2D), para exibir coleções de documentos. Esta metáfora visual utiliza círculos para representar grupos de documentos, onde o tamanho de cada círculo define a importância dos documentos no conjunto de dados.…”
Section: Escalabilidade Visualunclassified
“…O trabalho recentemente proposto por (PAGLIOSA et al, 2013) denominado Informação Multiescala e Sumarização de Texto (MIST) faz junção de duas abordagens, a word cloud e a rigid-body (Box2D), para exibir coleções de documentos. Esta metáfora visual utiliza círculos para representar grupos de documentos, onde o tamanho de cada círculo define a importância dos documentos no conjunto de dados.…”
Section: Escalabilidade Visualunclassified
“…Multidimensional Projection (MP) relies on dimensionality reduction theory to embed multidimensional data into a visual space. Thus, it allows the visual exploration of different types of data, such as, document collections (PAGLIOSA et al, 2013), image datasets (JOIA et al, 2012) or even scientific data such as vector fields (DANIELS et al, 2010). Formally, multidimensional projection methods can be defined as follows: Definição 1.…”
Section: Multidimensional Projectionmentioning
confidence: 99%