Visual comparative case analytics

Sacha, Dominik, Jentner, Wolfgang, Zhang, Leishi ORCID logoORCID: https://orcid.org/0000-0002-3158-2328, Stoffel, Florian and Ellis, Geoffrey (2017) Visual comparative case analytics. EuroVis Workshop on Visual Analytics (EuroVA). In: EuroVis Workshop on Visual Analytics, 12-13 June 2017, Barcelona, Spain. ISBN 9783038680420. [Conference or Workshop Item] (doi:10.2312/eurova.20171119)

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Abstract

Criminal Intelligence Analysis (CIA) faces a challenging task in handling high-dimensional data that needs to be investigated with complex analytical processes. State-of-the-art crime analysis tools do not fully support interactive data exploration and fall short of computational transparency in terms of revealing alternative results. In this paper we report our ongoing research into providing the analysts with such a transparent and interactive system for exploring similarities between crime cases. The system implements a computational pipeline together with a visual platform that allows the analysts to interact with each stage of the analysis process and to validate the result. The proposed Visual Analytics (VA) workflow iteratively supports the interpretation of obtained clustering results, the development of alternative models, as well as cluster verification. The visualizations offer a usable way for the analyst to provide feedback to the system and to observe the impact of their interactions

Item Type: Conference or Workshop Item (Paper)
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 21853
Notes on copyright: © 2017 The Author(s) Eurographics Proceedings
© 2017 The Eurographics Association.
The full text of the published version available in this repository (http://eprints.mdx.ac.uk/) in accordance with the Eurographics guidelines for authors.
The definitive version is available at http://diglib.eg.org/
Useful Links:
Depositing User: Leishi Zhang
Date Deposited: 23 May 2017 13:26
Last Modified: 12 Jun 2022 03:40
URI: https://eprints.mdx.ac.uk/id/eprint/21853

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