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DC poleHodnotaJazyk
dc.contributor.authorBernard, Jürgen
dc.contributor.authorSessler, David
dc.contributor.authorRuppert, Tobbias
dc.contributor.editorSkala, Václav
dc.date.accessioned2017-11-08T12:47:37Z
dc.date.available2017-11-08T12:47:37Z
dc.date.issued2014
dc.identifier.citationWSCG 2014: communication papers proceedings: 22nd International Conference in Central Europeon Computer Graphics, Visualization and Computer Visionin co-operation with EUROGRAPHICS Association, p. 329-338.en
dc.identifier.isbn978-80-86943-71-8
dc.identifier.uriwscg.zcu.cz/WSCG2014/!!_2014-WSCG-Communication.pdf
dc.identifier.urihttp://hdl.handle.net/11025/26431
dc.format10 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesWSCG 2014: communication papers proceedingsen
dc.rights@ Václav Skala - UNION Agencycs
dc.subjectopatřenícs
dc.subjectnávrh zaměřený na uživatelecs
dc.subjectuživatelská zpětná vazbacs
dc.subjectsmíšené data setycs
dc.subjectvýběr funkcícs
dc.subjectvizualizace informacícs
dc.subjectvizuální analýzacs
dc.titleUser-based visual-interactive similarity definition for mixed data objects: concept and first implementationen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedThe definition of similarity between data objects plays a key role in many analytical systems. The process of similarity definition comprises several challenges as three main problems occur: different stakeholders, mixed data, and changing requirements. Firstly, in many applications the developers of the analytical system (data scientists) model the similarity, while the users (domain experts) have distinct (mental) similarity notions. Secondly, the definition of similarity for mixed data types is challenging. Thirdly, many systems use static similarity models that cannot adapt to changing data or user needs. We present a concept for the development of systems that support the visual-interactive similarity definition for mixed data objects emphasizing 15 crucial steps. For each step different design considerations and implementation variants are presented, revealing a large design space. Moreover, we present a first implementation of our concept, enabling domain experts to express mental similarity notions through a visual-interactive system. The provided implementation tackles the different-stakeholders problem, the mixed data problem, and the changing requirements problem. The implementation is not limited to a specific mixed data set. However, we show the applicability of our implementation in a case study where a functional similarity model is trained for countries as objects.en
dc.subject.translatedmeasuresen
dc.subject.translateduser-centered designen
dc.subject.translateduser feedbacken
dc.subject.translatedmixed data setsen
dc.subject.translatedfeature selectionen
dc.subject.translatedinformation visualizationen
dc.subject.translatedvisual analyticsen
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:WSCG 2014: Communication Papers Proceedings

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