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dc.contributor.authorDudley, JJ
dc.contributor.authorJacques, JT
dc.contributor.authorKristensson, PO
dc.date.accessioned2019-02-02T00:31:19Z
dc.date.available2019-02-02T00:31:19Z
dc.date.issued2019
dc.identifier.isbn9781450359702
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/288721
dc.description.abstractDesigning novel interfaces is challenging. Designers typically rely on experience or subjective judgment in the absence of analytical or objective means for selecting interface parameters. We demonstrate Bayesian optimization as an efficient tool for objective interface feature refinement. Specifically, we show that crowdsourcing paired with Bayesian optimization can rapidly and effectively assist interface design across diverse deployment environments. Experiment 1 evaluates the approach on a familiar 2D interface design problem: a map search and review use case. Adding a degree of complexity, Experiment 2 extends Experiment 1 by switching the deployment environment to mobile-based virtual reality. The approach is then demonstrated as a case study for a fundamentally new and unfamiliar interaction design problem: web-based augmented reality. Finally, we show how the model generated as an outcome of the refinement process can be used for user simulation and queried to deliver various design insights.
dc.publisherACM
dc.titleCrowdsourcing interface feature design with Bayesian optimization
dc.typeConference Object
prism.publicationDate2019
prism.publicationNameConference on Human Factors in Computing Systems - Proceedings
dc.identifier.doi10.17863/CAM.35981
dcterms.dateAccepted2018-12-10
rioxxterms.versionofrecord10.1145/3290605.3300482
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2019-05-02
dc.contributor.orcidDudley, John [0000-0001-6692-4853]
dc.contributor.orcidJacques, Jason [0000-0003-3496-7060]
dc.contributor.orcidKristensson, Per Ola [0000-0002-7139-871X]
dc.publisher.urlhttps://doi.org/10.1145/3290605
rioxxterms.typeConference Paper/Proceeding/Abstract
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/R004471/1)
cam.issuedOnline2019-05-02
pubs.conference-nameCHI '19: CHI Conference on Human Factors in Computing Systems
pubs.conference-start-date2019-05-04
cam.orpheus.successThu Nov 05 11:53:24 GMT 2020 - Embargo updated
pubs.conference-finish-date2019-05-09
rioxxterms.freetoread.startdate2020-05-02


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