#Human-Computer Interaction
Publikationen
Luh, R., Schramm, G., Wagner, M., Janicke, H., & Schrittwieser, S. (2018). SEQUIN: a grammar inference framework for analyzing malicious system behavior. Journal of Computer Virology and Hacking Techniques, 01–21. https://doi.org/10.1007/s11416-018-0318-x
Bernard, J., Zeppelzauer, M., Sedlmair, M., & Aigner, W. (2018). VIAL – A Unified Process for Visual-Interactive Labeling. The Visual Computer, 16. https://doi.org/10.1007/s00371-018-1500-3
Streit, M., Aigner, W., & Girardi, D. (2018, March). Injecting Life into Visualizations for Biomedical Research. Presented at the DBMI Open Insights Seminar, Harvard University.
Aigner, W., Rind, A., & Wagner, M. (2018). KAVA-Time: Knowledge-Assisted Visual Analytics Methods for Time-Oriented Data. In Tagungsband des 12. Forschungsforum der österreichischen Fachhochschulen (FFH) 2018.
Michelberger, F. (2018, March). CargoRider - A new mobility service for cargo ships. Presented at the Successful R&I in Europe - 9th European Networking Event 2018, Düsseldorf, Germany.
Andrienko, N., Lammarsch, T., Andrienko, G., Fuchs, G., Keim, D. A., Miksch, S., & Rind, A. (2018). Viewing Visual Analytics as Model Building. Computer Graphics Forum, 37(6), 275–299. https://doi.org/10.1111/cgf.13324
Wagner, M., Slijepcevic, D., Horsak, B., Rind, A., Zeppelzauer, M., & Aigner, W. (2018). KAVAGait: Knowledge-Assisted Visual Analytics for Clinical Gait Analysis. IEEE Transactions on Visualization and Computer Graphics (TVCG), 25(3), 1528–1542. https://doi.org/10.1109/TVCG.2017.2785271
Rind, A., Iber, M., & Aigner, W. (2018). Bridging the Gap Between Sonification and Visualization. In Proc. AVI Workshop on Multimodal Interaction for Data Visualization (MultimodalVis).
Blauensteiner, B., & Michelberger, F. (2018). Cargo Rider - Attracting New Audiences for Cargo Ships. Presented at the Transport Research Arena (TRA) 2018, Vienna.
Niederer, C., Stitz, H., Hourieh, R., Grassinger, F., Aigner, W., & Streit, M. (2018). TACO: Visualizing Changes in Tables Over Time. IEEE Transactions on Visualization and Computer Graphics (InfoVis "17), 24(1), 677–686. https://doi.org/10.1109/TVCG.2017.2745298