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Expert-Guided Generative Topographical Modeling with Visual to Parametric Interaction

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dc.contributor.authorHan, Chaoen
dc.contributor.authorHouse, Leanna L.en
dc.contributor.authorLeman, Scotland C.en
dc.contributor.departmentStatisticsen
dc.date.accessioned2017-02-19T01:36:46Zen
dc.date.available2017-02-19T01:36:46Zen
dc.date.issued2016-02-23en
dc.description.abstractIntroduced by Bishop et al. in 1996, Generative Topographic Mapping (GTM) is a powerful nonlinear latent variable modeling approach for visualizing high-dimensional data. It has shown useful when typical linear methods fail. However, GTM still suffers from drawbacks. Its complex parameterization of data make GTM hard to fit and sensitive to slight changes in the model. For this reason, we extend GTM to a visual analytics framework so that users may guide the parameterization and assess the data from multiple GTM perspectives. Specifically, we develop the theory and methods for Visual to Parametric Interaction (V2PI) with data using GTM visualizations. The result is a dynamic version of GTM that fosters data exploration. We refer to the new version as V2PI-GTM. In this paper, we develop V2PI-GTM in stages and demonstrate its benefits within the context of a text mining case study.en
dc.description.versionPublished versionen
dc.format.extent? - ? (14) page(s)en
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0129122en
dc.identifier.issn1932-6203en
dc.identifier.issue2en
dc.identifier.urihttp://hdl.handle.net/10919/75064en
dc.identifier.volume11en
dc.languageEnglishen
dc.publisherPLOSen
dc.relation.urihttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000371163000001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=930d57c9ac61a043676db62af60056c1en
dc.rightsCreative Commons CC0 1.0 Universal Public Domain Dedicationen
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/en
dc.titleExpert-Guided Generative Topographical Modeling with Visual to Parametric Interactionen
dc.title.serialPLOS ONEen
dc.typeArticle - Refereeden
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Scienceen
pubs.organisational-group/Virginia Tech/Science/COS T&R Facultyen
pubs.organisational-group/Virginia Tech/Science/Statisticsen

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