Publikation: A Visual Analytics Approach for Crime Signature Generation and Exploration
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2016
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Published
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IEEE VIS2016 Workshop on Temporal & Sequential Event Analysis : Papers. 2016
Zusammenfassung
The exploration of volumes of crime reports is a tedious task in crime intelligence analysis, given the largely unstructured nature of the crime descriptions. This paper describes a Visual Analytics approach for crime signature exploration that tightly integrates automated event sequence extraction and signature mining with interactive visualization. We describe the major components of our analysis pipeline — crime concept/event extraction, crime sequence mining, and interactive visualization. We illustrate its applicability with a real world use case. Finally, we discuss current problems, future plans, and open challenges in our development of a solution that incorporates automated event pattern mining with human expert feedback.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
Event extraction, sequence mining, event analysis, interactive visualization, visual analytics, crime analysis
Konferenz
IEEE VIS2016 Workshop on Temporal & Sequential Event Analysis, 24. Okt. 2016, Baltimore, USA
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ISO 690
JENTNER, Wolfgang, Geoffrey ELLIS, Florian STOFFEL, Dominik SACHA, Daniel A. KEIM, 2016. A Visual Analytics Approach for Crime Signature Generation and Exploration. IEEE VIS2016 Workshop on Temporal & Sequential Event Analysis. Baltimore, USA, 24. Okt. 2016. In: IEEE VIS2016 Workshop on Temporal & Sequential Event Analysis : Papers. 2016BibTex
@inproceedings{Jentner2016Visua-41296,
year={2016},
title={A Visual Analytics Approach for Crime Signature Generation and Exploration},
url={http://eventevent.github.io/papers/EVENT_2016_paper_24.pdf},
booktitle={IEEE VIS2016 Workshop on Temporal & Sequential Event Analysis : Papers},
author={Jentner, Wolfgang and Ellis, Geoffrey and Stoffel, Florian and Sacha, Dominik and Keim, Daniel A.}
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<dcterms:abstract xml:lang="eng">The exploration of volumes of crime reports is a tedious task in crime intelligence analysis, given the largely unstructured nature of the crime descriptions. This paper describes a Visual Analytics approach for crime signature exploration that tightly integrates automated event sequence extraction and signature mining with interactive visualization. We describe the major components of our analysis pipeline — crime concept/event extraction, crime sequence mining, and interactive visualization. We illustrate its applicability with a real world use case. Finally, we discuss current problems, future plans, and open challenges in our development of a solution that incorporates automated event pattern mining with human expert feedback.</dcterms:abstract>
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URL der Originalveröffentl.
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2018-02-12
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