EuroVisPosters2016

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https://diglib.eg.org/handle/10.2312/15276

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Browsing EuroVisPosters2016 by Subject "General"

Now showing 1 - 3 of 3
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    InVITe - Towards Intuitive Visualization of Iterations over Text
    (The Eurographics Association, 2016) Lamqaddam, Houda; Aerts, Jan; Tobias Isenberg and Filip Sadlo
    With InVITe, we are working towards intuitive visualization to support review of iterative modifications on text documents. In order to accomplish this, we perform simple matching of text snippets between the two versions of text, across a large range of parameter settings. Next, an overview graphic indicating the effect of parameter space on the output allows the user to select those combinations that are of interest. Finally, such selection will display an alluvial diagram with annotations and covering different resolutions. With this tool, co-authors can keep an overview of changes made, both structural and local.
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    Tracking and Visualizing Dynamic Structures in Multichannel EEG Coherence Networks
    (The Eurographics Association, 2016) Ji, Chengtao; Gronde, J. J. van de; Maurits, N. M.; Roerdink, Jos B. T. M.; Tobias Isenberg and Filip Sadlo
    An electroencephalography (EEG) coherence network represents functional brain connectivity, and is constructed by calculating the coherence between pairs of electrode signals as a function of frequency. Visualization of coherence networks can provide insight into unexpected patterns of cognitive processing and help neuroscientists understand brain mechanisms. However, most studies have been limited to static EEG coherence networks or were focused on individual network nodes. In this poster, we consider groups of nodes for visualizing the evolution of network communities and their corresponding spatial location. We use a timeline-based representation to provide an overview of the evolution of functional units (FUs) and their corresponding spatial location over time. This representation can help the viewer identify functional units across the whole time window, as well as to identify relations between functional units and brain regions. In addition, a time-annotated FU map is provided to facilitate comparison of the behavior of the nodes between consecutive FU maps. This time-annotated FU map provides more detail about how the classification of electrodes into FUs changes over time. Our method is proposed as a first step towards a complete analysis of EEG coherence networks.
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    Visual Analysis of Text Annotations for Stance Classification with ALVA
    (The Eurographics Association, 2016) Kucher, Kostiantyn; Kerren, Andreas; Paradis, Carita; Sahlgren, Magnus; Tobias Isenberg and Filip Sadlo
    The automatic detection and classification of stance taking in text data using natural language processing and machine learning methods create an opportunity to gain insight about the writers' feelings and attitudes towards their own and other people's utterances. However, this task presents multiple challenges related to the training data collection as well as the actual classifier training. In order to facilitate the process of training a stance classifier, we propose a visual analytics approach called ALVA for text data annotation and visualization. Our approach supports the annotation process management and supplies annotators with a clean user interface for labeling utterances with several stance categories. The analysts are provided with a visualization of stance annotations which facilitates the analysis of categories used by the annotators. ALVA is already being used by our domain experts in linguistics and computational linguistics in order to improve the understanding of stance phenomena and to build a stance classifier for applications such as social media monitoring.