UofC-Bayes: A Bayesian Approach to Visualizing Uncertainty in Likert Scales

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dc.contributor.authorHornbeck, Haysn
dc.contributor.authorAlim, Usman
dc.date.accessioned2021-06-15T22:51:54Z
dc.date.available2021-06-15T22:51:54Z
dc.date.issued2019-10
dc.description.abstractDisasters demand a quick response based on incomplete information. For the Saint Himark dataset, part of the 2019 VAST Challenge, we focused on delivering a visualization which accurately conveyed that uncertainty. While our analysis was done offline, we chose techniques and algorithms which could easily be applied to realtime usage. Our visualization for the first mini-challenge was a one-screen dashboard that summarized citizen feedback.en_US
dc.description.grantingagencyNatural Sciences and Engineering Research Council (NSERC)en_US
dc.identifier.citationHornbeck, H., & Alim, U. (2019). UofC-Bayes: A Bayesian approach to visualizing uncertainty in Likert Scales. 2019 IEEE Conference on Visual Analytics Science and Technology (VAST). doi:10.1109/vast47406.2019.8986935en_US
dc.identifier.doihttp://dx.doi.org/10.1109/VAST47406.2019.8986935en_US
dc.identifier.grantnumberRGPIN-2019-05303en_US
dc.identifier.urihttp://hdl.handle.net/1880/113496
dc.identifier.urihttps://doi.org/10.11575/PRISM/46121
dc.publisher.departmentComputer Scienceen_US
dc.publisher.facultyScienceen_US
dc.publisher.hasversionacceptedVersionen_US
dc.publisher.institutionUniversity of Calgaryen_US
dc.rights© 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.en_US
dc.titleUofC-Bayes: A Bayesian Approach to Visualizing Uncertainty in Likert Scalesen_US
dc.typeconference posteren_US
ucalgary.item.requestcopyfalseen_US
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