EuroVA: International Workshop on Visual Analytics: Recent submissions

Now showing items 61-80 of 190

    • Contextualized Analysis of Movement Events 

      Chen, Siming; Andrienko, Gennady; Andrienko, Natalia; Doulkeridis, Christos; Koumparos, Athanasios (The Eurographics Association, 2019)
      For understanding the circumstances, causes, and consequences of events that may happen during movement (e.g., harsh brake, sharp turn), it is necessary to analyze event context. The context includes dynamic attributes of ...

    • Moving Together: Towards a Formalization of Collective Movement 

      Buchmüller, Juri; Cakmak, Eren; Andrienko, Natalia; Andrienko, Gennady; Jolles, Jolle W.; Keim, Daniel A. (The Eurographics Association, 2019)
      While conventional applications for spatiotemporal datasets mostly focus on the relation between movers and environment, research questions in the analysis of collective movement typically focus more on relationships and ...

    • On Quality Indicators for Progressive Visual Analytics 

      Angelini, Marco; May, Thorsten; Santucci, Giuseppe; Schulz, Hans-Jörg (The Eurographics Association, 2019)
      A key component in using Progressive Visual Analytics (PVA) is to be able to gauge the quality of intermediate analysis outcomes. This is necessary in order to decide whether a current partial outcome is already good enough ...

    • Visualization of Rubik's Cube Solution Algorithms 

      Steinparz, Christian Alexander; Hinterreiter, Andreas; Stitz, Holger; Streit, Marc (The Eurographics Association, 2019)
      Rubik's Cube is among the world's most famous puzzle toys. Despite its relatively simple principle, it requires dedicated, carefully planned algorithms to be solved. In this paper, we present an approach to visualize how ...

    • Quantifying Uncertainty in Multivariate Time Series Pre-Processing 

      Bors, Christian; Bernard, Jürgen; Bögl, Markus; Gschwandtner, Theresia; Kohlhammer, Jörn; Miksch, Silvia (The Eurographics Association, 2019)
      In multivariate time series analysis, pre-processing is integral for enabling analysis, but inevitably introduces uncertainty into the data. Enabling the assessment of the uncertainty and allowing uncertainty-aware analysis, ...

    • Deep Learning Inverse Multidimensional Projections 

      Espadoto, Mateus; Rodrigues, Francisco Caio Maia; Hirata, Nina S. T.; Hirata Jr., Roberto; Telea, Alexandru C. (The Eurographics Association, 2019)
      We present a new method for computing inverse projections from 2D spaces to arbitrary high-dimensional spaces. Given any projection technique, we train a deep neural network to learn a low-to-high dimensional mapping based ...

    • TourDino: A Support View for Confirming Patterns in Tabular Data 

      Eckelt, Klaus; Adelberger, Patrick; Zichner, Thomas; Wernitznig, Andreas; Streit, Marc (The Eurographics Association, 2019)
      Seeking relationships and patterns in tabular data is a common data exploration task. To confirm hypotheses that are based on visual patterns observed during exploratory data analysis, users need to be able to quickly ...

    • Visual Analysis of Degree-of-Interest Functions to Support Selection Strategies for Instance Labeling 

      Bernard, Jürgen; Hutter, Marco; Ritter, Christian; Lehmann, Markus; Sedlmair, Michael; Zeppelzauer, Matthias (The Eurographics Association, 2019)
      Manually labeling data sets is a time-consuming and expensive task that can be accelerated by interactive machine learning and visual analytics approaches. At the core of these approaches are strategies for the selection ...

    • EuroVa 2019: Frontmatter 

      Landesberger, Tatiana; Turkay, Cagatay (The Eurographics Association, 2019)

    • A Concept for Consensus-based Ordering of Views 

      Jentner, Wolfgang; Jäckle, Dominik; Engelke, Ulrich; Keim, Daniel A.; Schreck, Tobias (The Eurographics Association, 2018)
      High-dimensional data poses a significant challenge for analysis, as patterns typically exist only in subsets of dimensions or records. A common approach to reveal patterns, such as meaningful structures or relationships, ...

    • Towards Visual Cyber Security Analytics for the Masses 

      Ulmer, Alex; Schufrin, Marija; Lücke-Tieke, Hendrik; Kannanayikkal, Clindo Devassy; Kohlhammer, Jörn (The Eurographics Association, 2018)
      Understanding network activity and cyber threats is of major concern these days, for business and private users alike. As more and more online applications assist us in our daily life, there is a growing potential vulnerability ...

    • Combining the Automated Segmentation and Visual Analysis of Multivariate Time Series 

      Bernard, Jürgen; Bors, Christian; Bögl, Markus; Eichner, Christian; Gschwandtner, Theresia; Miksch, Silvia; Schumann, Heidrun; Kohlhammer, Jörn (The Eurographics Association, 2018)
      For the automatic segmentation of multivariate time series domain experts at first need to consider a huge space of alternative configurations of algorithms and parameters. We assume that only a small subset of these ...

    • polimaps: Supporting Predictive Policing with Visual Analytics 

      Stoffel, Florian; Post, Hanna; Stewen, Marcus; Keim, Daniel A. (The Eurographics Association, 2018)
      Recently, predictive policing has gained a lot of attention, as the benefits, e.g., better crime prevention or an optimized resource planning are essential goals for law enforcement agencies. Commercial predictive policing ...

    • A Set-based Visual Analytics Approach to Analyze Retail Data 

      Adnan, Muhammad; Ruddle, Roy A. (The Eurographics Association, 2018)
      This paper explores how a set-based visual analytics approach could be useful for analyzing customers' shopping behavior, and makes three main contributions. First, it describes the scale and characteristics of a real-world ...

    • Personalized Visual-Interactive Music Classification 

      Ritter, Christian; Altenhofen, Christian; Zeppelzauer, Matthias; Kuijper, Arjan; Schreck, Tobias; Bernard, Jürgen (The Eurographics Association, 2018)
      We present an interactive visual music classification tool that will allow users to automatically structure music collections in a personalized way. With our approach, users play an active role in an iterative process of ...

    • A Visual Analytics System for Managing Mobile Network Failures 

      Angelini, Marco; Bardone, Luca; Geymonat, Marina; Mirabelli, Mario; Remondino, Chiara; Santucci, Giuseppe; Stabellini, Barbara; Tamborrini, Paolo (The Eurographics Association, 2018)
      Large mobile operators have to quickly react to mobile network failures to ensure service continuity and this task is a complex one, due to the continuous and very fast evolution of mobile networks: from 2G to 3G and onto ...

    • Guidance or No Guidance? A Decision Tree Can Help 

      Ceneda, Davide; Gschwandtner, Theresia; May, Thorsten; Miksch, Silvia; Streit, Marc; Tominski, Christian (The Eurographics Association, 2018)
      Guidance methods have the potential of bringing considerable benefits to Visual Analytics (VA), alleviating the burden on the user and allowing a positive analysis outcome. However, the boundary between conventional VA ...

    • Visual Predictive Analytics using iFuseML 

      Sehgal, Gunjan; Rawat, Mrinal; Gupta, Bindu; Gupta, Garima; Sharma, Geetika; Shroff, Gautam (The Eurographics Association, 2018)
      Solving a predictive analytics problem involves multiple machine learning tasks in a workflow. Directing such workflows efficiently requires an understanding of data so as to identify and handle missing values and outliers, ...

    • Visual Exploration of Spatial and Temporal Variations of Tweet Topic Popularity 

      Li, Jie; Chen, Siming; Andrienko, Gennady; Andrienko, Natalia (The Eurographics Association, 2018)
      We present a visual analytical approach to exploring variation of topic popularity in social media (such as Twitter) over space and time. Our approach includes an analytical pipeline and a multi-view visualization tool. ...

    • ComModeler: Topic Modeling Using Community Detection 

      Dang, Tommy; Nguyen, Vinh The (The Eurographics Association, 2018)
      This paper introduces ComModeler, a novel approach for topic modeling using community finding in dynamic networks. Our algorithm first extracts the terms/keywords, formulates a network of collocated terms, then refines the ...