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dc.contributor.authorSchmid, Jennyen_US
dc.contributor.authorCibulski, Lenaen_US
dc.contributor.authorHazwani, Ibrahim Alen_US
dc.contributor.authorBernard, Jürgenen_US
dc.contributor.editorBernard, Jürgenen_US
dc.contributor.editorAngelini, Marcoen_US
dc.description.abstractItem rankings are useful when a decision needs to be made, especially if there are multiple attributes to be considered. However, existing tools either do not support both categorical and numerical attributes, require programming expertise for expressing preferences on attributes, do not offer instant feedback, or lack flexibility in expressing various types of user preferences. In this work, we present RankASco: a human-centered visual analytics approach that supports the interactive and visual creation of rankings. RankASco leverages a series of visual interfaces, enabling broad user groups to a) select attributes of interest, b) express preferences on attribute scorings based on different mental models, and c) analyze and refine item ranking results.en_US
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.titleRankASco: A Visual Analytics Approach to Leverage Attribute-Based User Preferences for Item Rankingsen_US
dc.description.seriesinformationEuroVis Workshop on Visual Analytics (EuroVA)
dc.description.sectionheadersHuman-Model Collaboration and Personalization
dc.identifier.pages5 pages

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Attribution 4.0 International License
Except where otherwise noted, this item's license is described as Attribution 4.0 International License