Dziban: Balancing Agency & Automation in Visualization Design via Anchored Recommendations

CHI '20: CHI Conference on Human Factors in Computing Systems Honolulu HI USA April, 2020, pp. 1-12, 2020.

Cited by: 1|Bibtex|Views88|DOI:https://doi.org/10.1145/3313831.3376880
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Other Links: dl.acm.org|dblp.uni-trier.de|academic.microsoft.com

Abstract:

Visualization recommender systems attempt to automate design decisions spanning choices of selected data, transformations, and visual encodings. However, across invocations such recommenders may lack the context of prior results, producing unstable outputs that override earlier design choices. To better balance automated suggestions with ...More

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