Bremm, Sebastian ; Landesberger von Antburg, Tatiana ; Bernard, Jürgen ; Schreck, Tobias (2011)
Assisted Descriptor Selection Based on Visual Comparative Data Analysis.
In: Computer Graphics Forum, 30 (3)
doi: 10.1111/j.1467-8659.2011.01938.x
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
Exploration and selection of data descriptors representing objects using a set of features are important components in many data analysis tasks. Usually, for a given dataset, an optimal data description does not exist, as the suitable data representation is strongly use case dependent. Many solutions for selecting a suitable data description have been proposed. In most instances, they require data labels and often are black box approaches. Non-expert users have difficulties to comprehend the coherency of input, parameters, and output of these algorithms. Alternative approaches, interactive systems for visual feature selection, overburden the user with an overwhelming set of options and data views. Therefore, it is essential to offer the users guidance in this analytical process. In this paper, we present a novel system for data description selection, which facilitates the user's access to the data analysis process. As finding of suitable data description consists of several steps, we support the user with guidance. Our system combines automatic data analysis with interactive visualizations. By this, the system provides a recommendation for suitable data descriptor selections. It supports the comparison of data descriptors with differing dimensionality for unlabeled data. We propose specialized scores and interactive views for descriptor comparison. The visualization techniques are scatterplot-based and grid-based. For the latter case, we apply Self-Organizing Maps as adaptive grids which are well suited for large multi-dimensional data sets. As an example, we demonstrate the usability of our system on a real-world biochemical application.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2011 |
| Autor(en): | Bremm, Sebastian ; Landesberger von Antburg, Tatiana ; Bernard, Jürgen ; Schreck, Tobias |
| Art des Eintrags: | Bibliographie |
| Titel: | Assisted Descriptor Selection Based on Visual Comparative Data Analysis |
| Sprache: | Englisch |
| Publikationsjahr: | 2011 |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | Computer Graphics Forum |
| Jahrgang/Volume einer Zeitschrift: | 30 |
| (Heft-)Nummer: | 3 |
| DOI: | 10.1111/j.1467-8659.2011.01938.x |
| Kurzbeschreibung (Abstract): | Exploration and selection of data descriptors representing objects using a set of features are important components in many data analysis tasks. Usually, for a given dataset, an optimal data description does not exist, as the suitable data representation is strongly use case dependent. Many solutions for selecting a suitable data description have been proposed. In most instances, they require data labels and often are black box approaches. Non-expert users have difficulties to comprehend the coherency of input, parameters, and output of these algorithms. Alternative approaches, interactive systems for visual feature selection, overburden the user with an overwhelming set of options and data views. Therefore, it is essential to offer the users guidance in this analytical process. In this paper, we present a novel system for data description selection, which facilitates the user's access to the data analysis process. As finding of suitable data description consists of several steps, we support the user with guidance. Our system combines automatic data analysis with interactive visualizations. By this, the system provides a recommendation for suitable data descriptor selections. It supports the comparison of data descriptors with differing dimensionality for unlabeled data. We propose specialized scores and interactive views for descriptor comparison. The visualization techniques are scatterplot-based and grid-based. For the latter case, we apply Self-Organizing Maps as adaptive grids which are well suited for large multi-dimensional data sets. As an example, we demonstrate the usability of our system on a real-world biochemical application. |
| Freie Schlagworte: | Forschungsgruppe Visual Search and Analysis (VISA), Business Field: Visual decision support, Research Area: Generalized digital documents, Interactive visualization, Feature selection, Self-organizing maps (SOM) |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 12 Nov 2018 11:16 |
| Letzte Änderung: | 22 Jul 2021 18:31 |
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