An Application of Edge Bundling Techniques to the Visualization of Media Analysis Results

The advent of consumer-generated and social media has led to a continuous expansion and diversification of the media landscape. Media consumers frequently find themselves assuming the role of media analysts in order to satisfy personal information needs. We propose to employ Knowledge Visualization methods in support of complex media analysis tasks. In this paper, we describe an approach which depicts semantic relationships between key political actors using node-link diagrams. Our contribution comprises a force-directed edge bundling algorithm which accounts for semantic properties of edges, a technical evaluation of the algorithm and a report on a real-world application of the approach. The resulting visualization fosters the identification of high-level edge patterns which indicate strong semantic relationships. It has been published by the Austrian Press Agency APA in 2009

On the beauty and usability of tag clouds

Tag clouds are text-based visual representations of a set of tags usually depicting tag importance by font size. Recent trends in social and collaborative software have greatly increased the popularity of this type of visualization. This paper proposes a family of novel algorithms for tag cloud layout and presents evaluation results obtained from an extensive user study and a technical evaluation. The algorithms address issues found in many common approaches, for example large whitespaces, overlapping tags and restriction to specific boundaries. The layouts computed by these algorithms are compact and clear, have small whitespaces and may feature arbitrary convex polygons as boundaries. The results of the user study and the technical evaluation enable designers to devise a combination of algorithm and parameters which produces satisfying tag cloud layouts for many application scenarios

Stress Maps: Analysing Local Phenomena in Dimensionality Reduction Based Visualizations

Challenges in Visual Analytics frequently involve massive repositories, which do not only contain a large number of information artefacts, but also a high number of relevant dimensions per artefact. Dimensionality reduction algorithms are commonly used to transform high-dimensional data into low- dimensional representations which are suitable for visualisation purposes. For example, Information Landscapes visualise high-dimensional data in two dimensions using distance-preserving projection methods. The inaccuracies introduced by such methods are usually expressed through a global stress measure which does not provide insight into localised phenomena. In this paper, we propose the use of Stress Maps, a combination of heat maps and information landscapes, to support algorithm development and optimization based on local stress measures. We report on an application of Stress Maps to a scalable text projection algorithm and describe two categories of problems related to localised stress phenomena which we have identified using the proposed method

Cross Media Retrieval in Knowledge Discovery

Abstract. Recent trends show that more and more digital cameras, video cameras and DVD recorders are sold and the number of emails and other messages sent increases each year. For example it is estimated that there will be nearly 300 million digital image capture devices in use worldwide through 2004, capturing about 29 billion digital pictures [12]. Users not only produce huge amounts of content, but this content is also spread over many different media types and document formats. Storing all contents implicates a great extent of documents in large, heterogeneous data repositories. Performing effective retrieval in heterogeneous repositories requires new approaches: documents in different formats containing different media types have to be transformed to a common denominator, and relations between contents of different media types must be established. This allows direct comparison of contents of different media types. In this paper we present a prototype called Magick that implements such an approach to cross-media retrieval