Now showing items 1-4 of 4

    • Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework 

      El-Assady, Mennatallah; Sevastjanova, Rita; Sperrle, Fabian; Keim, Daniel; Collins, Christopher (IEEE, 2017-08-29)
      Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, ...
    • The Role of Interactive Visualization in Fostering Trust in AI 

      Beauxis-Aussalet, Emma; Behrisch, Michael; Borgo, Rita; Chau, Duen Horng; Collins, Christopher; Ebert, David; El-Assady, Mennatallah; Endert, Alex; Keim, Daniel A.; Kohlhammer, Jörn; Oelke, Daniela; Peltonen, Jaakko; Riveiro, Maria; Schreck, Tobias; Strobelt, Hendrik; van Wijk, Jarke J. (IEEE, 2021-12-10)
      The increasing use of artificial intelligence (AI) technologies across application domains has prompted our society to pay closer attention to AI's trustworthiness, fairness, interpretability, and accountability. In order ...
    • Visual Analytics for Topic Model Optimization based on User-Steerable Speculative Execution 

      El-Assady, Mennatallah; Sperrle, Fabian; Deussen, Oliver; Keim, Daniel; Collins, Christopher (IEEE, 2018-09-18)
      To effectively assess the potential consequences of human interventions in model-driven analytics systems, we establish the concept of speculative execution as a visual analytics paradigm for creating user-steerable preview ...
    • Visualization and the Digital Humanities: Moving Toward Stronger Collaborations 

      Bradley, Adam James; El-Assady, Mennatallah; Coles, Katharine; Alexander, Eric; Chen, Min; Collins, Christopher; Jänicke, Stefan; Joseph, David (IEEE, 2018-12-01)
      For the past two years, researchers from the visualization community and the digital humanities have come together at the IEEE VIS conference to discuss how both disciplines can work together to push research goals in their ...