38-Issue 3

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https://diglib.eg.org/handle/10.2312/2632780

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Browsing 38-Issue 3 by Subject "concepts and paradigms"

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    Focus+Context Exploration of Hierarchical Embeddings
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Höllt, Thomas; Vilanova, Anna; Pezzotti, Nicola; Lelieveldt, Boudewijn P. F.; Hauser, Helwig; Gleicher, Michael and Viola, Ivan and Leitte, Heike
    Hierarchical embeddings, such as HSNE, address critical visual and computational scalability issues of traditional techniques for dimensionality reduction. The improved scalability comes at the cost of the need for increased user interaction for exploration. In this paper, we provide a solution for the interactive visual Focus+Context exploration of such embeddings. We explain how to integrate embedding parts from different levels of detail, corresponding to focus and context groups, in a joint visualization. We devise an according interaction model that relates typical semantic operations on a Focus+Context visualization with the according changes in the level-of-detail-hierarchy of the embedding, including also a mode for comparative Focus+Context exploration and extend HSNE to incorporate the presented interaction model. In order to demonstrate the effectiveness of our approach, we present a use case based on the visual exploration of multi-dimensional images.
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    Follow The Clicks: Learning and Anticipating Mouse Interactions During Exploratory Data Analysis
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Ottley, Alvitta; Garnett, Roman; Wan, Ran; Gleicher, Michael and Viola, Ivan and Leitte, Heike
    The goal of visual analytics is to create a symbiosis between human and computer by leveraging their unique strengths. While this model has demonstrated immense success, we are yet to realize the full potential of such a human-computer partnership. In a perfect collaborative mixed-initiative system, the computer must possess skills for learning and anticipating the users' needs. Addressing this gap, we propose a framework for inferring attention from passive observations of the user's click, thereby allowing accurate predictions of future events. We demonstrate this technique with a crime map and found that users' clicks can appear in our prediction set 92% - 97% of the time. Further analysis shows that we can achieve high prediction accuracy typically after three clicks. Altogether, we show that passive observations of interaction data can reveal valuable information that will allow the system to learn and anticipate future events.
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    Multiple Views: Different Meanings and Collocated Words
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Roberts, Jonathan; Al-Maneea, Hayder; Butcher, Peter; Lew, Robert; Rees, Geraint Paul; Sharma, Nirwan; Frankenberg-Garcia, Ana; Gleicher, Michael and Viola, Ivan and Leitte, Heike
    We report on an in-depth corpus linguistic study on 'multiple views' terminology and word collocation. We take a broad interpretation of these terms, and explore the meaning and diversity of their use in visualisation literature. First we explore senses of the term 'multiple views' (e.g.,'multiple views' can mean juxtaposition, many viewport projections or several alternative opinions). Second, we investigate term popularity and frequency of occurrences, investigating usage of 'multiple' and 'view' (e.g., multiple views, multiple visualisations, multiple sets). Third, we investigate word collocations and terms that have a similar sense (e.g., multiple views, side-by-side, small multiples). We built and used several corpora, including a 6-million-word corpus of all IEEE Visualisation conference articles published in IEEE Transactions on Visualisation and Computer Graphics 2012 to 2017. We draw on our substantial experience from early work in coordinated and multiple views, and with collocation analysis develop several lists of terms. This research provides insight into term use, a reference for novice and expert authors in visualisation, and contributes a taxonomy of 'multiple view' terms.