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Towards a User-Defined Visual-Interactive Definition of Similarity Functions for Mixed Data

Bernard, Jürgen and Hutter, Marco and Sessler, David and Schreck, Tobias and Behrisch, Michael and Kohlhammer, Jörn (2014):
Towards a User-Defined Visual-Interactive Definition of Similarity Functions for Mixed Data.
IEEE Computer Society, Los Alamitos, Calif., In: IEEE Conference on Visual Analytics Science and Technology. Proceedings, DOI: 10.1109/VAST.2014.7042503,
[Conference or Workshop Item]

Abstract

The creation of similarity functions based on visual-interactive user feedback is a promising means to capture the mental similarity notion in the heads of domain experts. In particular, concepts exist where users arrange multivariate data objects on a 2D data landscape in order to learn new similarity functions. While systems that incorporate numerical data attributes have been presented in the past, the remaining overall goal may be to develop systems also for mixed data sets. In this work, we present a feedback model for categorical data which can be used alongside of numerical feedback models in future.

Item Type: Conference or Workshop Item
Erschienen: 2014
Creators: Bernard, Jürgen and Hutter, Marco and Sessler, David and Schreck, Tobias and Behrisch, Michael and Kohlhammer, Jörn
Title: Towards a User-Defined Visual-Interactive Definition of Similarity Functions for Mixed Data
Language: English
Abstract:

The creation of similarity functions based on visual-interactive user feedback is a promising means to capture the mental similarity notion in the heads of domain experts. In particular, concepts exist where users arrange multivariate data objects on a 2D data landscape in order to learn new similarity functions. While systems that incorporate numerical data attributes have been presented in the past, the remaining overall goal may be to develop systems also for mixed data sets. In this work, we present a feedback model for categorical data which can be used alongside of numerical feedback models in future.

Publisher: IEEE Computer Society, Los Alamitos, Calif.
Uncontrolled Keywords: Business Field: Visual decision support, Business Field: Digital society, Research Area: Computer vision (CV), Research Area: Human computer interaction (HCI), Visual analytics, Information visualization, Similarity measures, Similarity metrics, Similarity search
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Event Title: IEEE Conference on Visual Analytics Science and Technology. Proceedings
Date Deposited: 12 Nov 2018 11:16
DOI: 10.1109/VAST.2014.7042503
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