Název:	User-based visual-interactive similarity definition for mixed data objects: concept and first implementation
Autoři:	Bernard, Jürgen Sessler, David Ruppert, Tobbias
Citace zdrojového dokumentu:	WSCG 2014: communication papers proceedings: 22nd International Conference in Central Europeon Computer Graphics, Visualization and Computer Visionin co-operation with EUROGRAPHICS Association, p. 329-338.
Datum vydání:	2014
Nakladatel:	Václav Skala - UNION Agency
Typ dokumentu:	konferenční příspěvek conferenceObject
URI:	wscg.zcu.cz/WSCG2014/!!_2014-WSCG-Communication.pdf http://hdl.handle.net/11025/26431
ISBN:	978-80-86943-71-8
Klíčová slova:	opatření;návrh zaměřený na uživatele;uživatelská zpětná vazba;smíšené data sety;výběr funkcí;vizualizace informací;vizuální analýza
Klíčová slova v dalším jazyce:	measures;user-centered design;user feedback;mixed data sets;feature selection;information visualization;visual analytics
Abstrakt v dalším jazyce:	The 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.
Práva:	@ Václav Skala - UNION Agency
Vyskytuje se v kolekcích:	WSCG 2014: Communication Papers Proceedings

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