Topigraphy

Fujimura, Kikuo; Fujimura, Shigeru; Matsubayashi, Tatsushi; Yamada, Takeshi; Okuda, Hiroyuki

doi:10.1145/1367497.1367669

Cited by 43 publications

(2 citation statements)

References 3 publications

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“…Entre las propuestas presentes en la literatura científica podemos destacar el uso de metáforas topográficas (Fujimura et al, 2008), el geoposicionamiento de tags (Tag-Maps) (Slingsby, Dykes, Wood, Clarke, 2007), el uso del enfoque de los diagramas de Venn para representar grupos de tags y sus relaciones (TagClusters) (Chen, Santamaría, Butz, Therón, 2009), la representación mediante mapas SOM (Self-Organizing Map) (Risi, Mörchen, Ultsch, Lewark, 2007;Lehwark, Risi, Ultsch, 2008), los ClusterMaps (Klerkx, Duval, 2009), y la presentación en forma de grafos arbóreos (tagFlake) (Caro, Candan, Sapino, 2008) y (TreeCloud) (Gambette, Véronis, 2009). Otros trabajos, como el de Kaser y Lemire (2007), ofrecen diversos algoritmos, tanto para la distribución espacial optimizada en tag-clouds tradicionales, como para la representación de relaciones entre tags.…”

Section: Modelos Visuales Alternativosunclassified

Usabilidad de los tag-clouds: estudio mediante eye-tracking.

Montero¹,

Herrero-Solana²,

Guerrero‐Bote³

2010

Scire

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Los tag-clouds, o nubes de etiquetas, son componentes de interfaz en forma de lista compacta de palabras clave, que permiten al usuario explorar y navegar por conjuntos documentales. Si bien en los últimos años han gozado de gran popularidad en el entorno Web, también es cierto que, como interfaces visuales de recuperación de información, presentan evidentes problemas de usabilidad. El presente trabajo se propone indagar en la usabilidad de los tag-clouds, a través de la revisión bibliográfica y un estudio con usuarios utilizando técnicas de eye-tracking o seguimiento visual. Los resultados demuestran que tanto el tamaño de fuente como la forma del tag-cloud tienen una clara influencia en la exploración visual de los usuarios. Respecto a la ordenación de los tags, si bien la ordenación alfabética no ofrece ventajas en tareas de búsqueda exploratoria, los resultados sugieren que la agrupación semántica tampoco supone una mejora en términos de eficiencia en tareas de localización visual de los tags. Finalmente se proponen posibles mejoras en la presentación de los tag-clouds agrupados semánticamente, así como futuras líneas de investigación

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Section: Modelos Visuales Alternativosunclassified

Usabilidad de los tag-clouds: estudio mediante eye-tracking.

Montero¹,

Herrero-Solana²,

Guerrero‐Bote³

2010

Scire

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“…Other approaches have considered multidimensional scaling [4,6] or factor analysis [2,19] to express the semantic proximity by displaying the most frequent words in two or three dimensions. However, these visualisations are often quite complex, and difficult to read and analyze quickly.…”

Section: Introductionmentioning

confidence: 99%

Visualising a Text with a Tree Cloud

Gambette

Véronis²

2010

Studies in Classification, Data Analysis, and Knowledge Organization

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Summary. Tag clouds have gained popularity over the internet to provide a quick overview of the content of a website or a text. We introduce a new visualisation which displays more information: the tree cloud. Like a word cloud, it shows the most frequent words of the text, where the size reflects the frequency, but the words are arranged on a tree to reflect their semantic proximity according to the text. Such tree clouds help identify the main topics of a document, and even be used for text analysis. We also provide methods to evaluate the quality of the obtained tree cloud, and some key steps of its construction. Our algorithms are implemented in the free software TreeCloud available at http://www.treecloud.org.

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Exploring New Ways of Utilizing Automated Clustering and Machine Learning Techniques in Information Visualization

Schrammel

2011

Human-Computer Interaction – INTERACT 2011

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Research Area: Information visualization, human-computer interaction.Research Topic. The main research topic of the thesis is to explore the possibilities of automated clustering and machine learning techniques for developing new approaches in information visualization.Research Problem. The main goal of information visualization is to present data to the users in a way that optimizes intelligibility of the data and support the detection of relevant patterns in the data, where the application context defines what qualifies as 'relevant'. Many different approaches typically tailored to a specific problem have been developed within the past years. At the same time the application of mathematical methods for data analysis and identification of patterns has substantially increased, and is typically referred to as data mining. Different visualization techniques are used in data mining, however the systematic and dynamic integration of data mining techniques with visualization approaches is only in its beginning.The main research problem tackled in the thesis is how to best integrate approaches from traditional data mining and information visualization domains to achieve more usable and helpful analysis tools for large amounts of data. The basic visualization approach explored is tag clouds, and especially concepts in displaying them according to a semantic structure as proposed e.g. by [2,3,1] are further developed. The overall research problem can be divided into sub-problems which need to be addressed in order to develop actually useful approaches:• Develop new approaches and concepts for integrating data mining and information visualization techniques • Develop a detailed understanding of the human perception and analysis process involved when interacting with these systems • Develop a understanding on the impact of errors, artifacts and imperfection in the data analysis on experienced quality and usefulness • Define quality benchmarks that are needed to be met to provide real value and benefit to the user when using such systems • Evaluate the developed concepts and prototypes in realistic scenarios, to be able to estimate their value and applicability in real-world contexts.

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Topigraphy

Cited by 43 publications

References 3 publications

Usabilidad de los tag-clouds: estudio mediante eye-tracking.

Usabilidad de los tag-clouds: estudio mediante eye-tracking.

Visualising a Text with a Tree Cloud

Exploring New Ways of Utilizing Automated Clustering and Machine Learning Techniques in Information Visualization

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