dc.contributor.author | Riehmann, Patrick | en_US |
dc.contributor.author | Schädler, Andreas | en_US |
dc.contributor.author | Harder, Jannis | en_US |
dc.contributor.author | Herpel, Jakob | en_US |
dc.contributor.author | Froehlich, Bernd | en_US |
dc.contributor.editor | Kerren, Andreas and Garth, Christoph and Marai, G. Elisabeta | en_US |
dc.date.accessioned | 2020-05-24T13:51:57Z | |
dc.date.available | 2020-05-24T13:51:57Z | |
dc.date.issued | 2020 | |
dc.identifier.isbn | 978-3-03868-106-9 | |
dc.identifier.uri | https://doi.org/10.2312/evs.20201042 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/evs20201042 | |
dc.description.abstract | We present an interactive visualization aiding users in making informed decisions about large product data sets consisting of quantitative and categorical attributes. Our approach tries to overcome common problems between parallel attribute axes, for instance limited horizontal space or clutter, by introducing novel visual concepts such as proxy axes, fusion axes, and hybrids of set-based and individual axis connections. A proxy axis represents a group of semantically related attributes, which can be interactively explored and seamlessly integrated into the display. Fusion axes allow users to reduce the number of axes by merging categorical+categorical or categorical+quantitative attribute axes. Set-based or individual connections between axis pairs are chosen according to the involved attribute types. The pilot study and expert reviews showed that these novel concepts are understood, considered to be very useful and favored over up-to-date webshop interfaces. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.rights | Attribution 4.0 International License | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | ] |
dc.subject | Human centered computing | |
dc.subject | Visualization techniques | |
dc.subject | Information visualization | |
dc.subject | Visualization theory | |
dc.subject | concepts and paradigms | |
dc.title | Configuration Finder: A Tidy Visual Interface for Effective Faceted Search | en_US |
dc.description.seriesinformation | EuroVis 2020 - Short Papers | |
dc.description.sectionheaders | Analytics and Evaluation | |
dc.identifier.doi | 10.2312/evs.20201042 | |
dc.identifier.pages | 19-23 | |