Visual Comparative Case Analytics
Date
2017Author
Sacha, Dominik
Jentner, Wolfgang
Zhang, Leishi
Stoffel, Florian
Ellis, Geoffrey
Metadata
Show full item recordAbstract
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.
BibTeX
@inproceedings {10.2312:eurova.20171119,
booktitle = {EuroVis Workshop on Visual Analytics (EuroVA)},
editor = {Michael Sedlmair and Christian Tominski},
title = {{Visual Comparative Case Analytics}},
author = {Sacha, Dominik and Jentner, Wolfgang and Zhang, Leishi and Stoffel, Florian and Ellis, Geoffrey},
year = {2017},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-042-0},
DOI = {10.2312/eurova.20171119}
}
booktitle = {EuroVis Workshop on Visual Analytics (EuroVA)},
editor = {Michael Sedlmair and Christian Tominski},
title = {{Visual Comparative Case Analytics}},
author = {Sacha, Dominik and Jentner, Wolfgang and Zhang, Leishi and Stoffel, Florian and Ellis, Geoffrey},
year = {2017},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-042-0},
DOI = {10.2312/eurova.20171119}
}
URI
http://dx.doi.org/10.2312/eurova.20171119https://diglib.eg.org:443/handle/10.2312/eurova20171119