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Mining multi-modal crime patterns at different levels of granularity using hierarchical clustering

conference contribution
posted on 2008-01-01, 00:00 authored by Yee Ling Boo, D Alahakoon
The appearance of patterns could be found in different modalities of a domain, where the different modalities refer to the data sources that constitute different aspects of a domain. Particularly, the domain of our discussion refers to crime and the different modalities refer to the different data sources such as offender data, weapon data, etc. in crime domain. In addition, patterns also exist in different levels of granularity for each modality. In order to have a thorough understanding a domain, it is important to reveal the hidden patterns through the data explorations at different levels of granularity and for each modality. Therefore, this paper presents a new model for identifying patterns that exist in different levels of granularity for different modes of crime data. A hierarchical clustering approach - growing self organising maps (GSOM) has been deployed. Furthermore, the model is enhanced with experiments that exhibit the significance of exploring data at different granularities.

History

Event

Computational Intelligence for Modelling, Control and Automation. Conference (2008 : Vienna, Austria)

Pagination

1268 - 1273

Publisher

IEEE

Location

Vienna, Austria

Place of publication

Piscataway, N.J.

Start date

2008-12-10

End date

2008-12-12

ISBN-13

9780769535142

Language

eng

Notes

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Publication classification

E1.1 Full written paper - refereed

Copyright notice

2008, IEEE

Title of proceedings

CIMCA 2008 : Proceeding of the 2008 International Conference on Computational Intelligence for Modelling, Control and Automation, December 10-12, 2008, Vienna, Austria

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