An exploration into the power of Formal Concept Analysis for domestic violence analysis

Authors
Publication date 2008
Host editors
  • P. Perner
Book title Advances in Data Mining. Medical Applications, E-Commerce, Marketing, and Theoretical Aspects
Book subtitle 8th Industrial Conference, ICDM 2008 Leipzig, Germany, July 16-18, 2008 : proceedings
ISBN
  • 9783540707172
ISBN (electronic)
  • 9783540707202
Series Lecture Notes in Computer Science
Event Advances in data mining: 8th industrial conference, ICDM 2008, Leipzig
Pages (from-to) 404-416
Publisher Berlin: Springer
Organisations
  • Faculty of Economics and Business (FEB) - Amsterdam Business School Research Institute (ABS-RI)
Abstract
The types of police inquiries performed are very diverse in nature and the current data processing architecture is not sufficiently tailored to cope with this diversity. Many information concerning cases is still stored in databases as unstructured text. Formal Concept Analysis is showcased as an exploratory data analysis technique for discovering new knowledge from police reports. It turns out that it provides a powerful framework for exploring the dataset, resulting in essential knowledge for improving current practices. It is shown that the domestic violence definition employed by the police organisation of the Netherlands is not always as clear as it should be, making it hard to use it effectively for classification purposes. In addition, newly discovered knowledge for automatically classifying certain cases as either domestic or non-domestic violence is presented. Moreover, essential techniques for detecting incorrect classifications, performed by police officers, are provided. Finally, some problems encountered because of the sometimes unstructured way of working of police officers are discussed. Both using Formal Concept Analysis for exploratory data analysis and its application on this area are novel enough to make this paper into a valuable contribution to the literature.
Document type Conference contribution
Language English
Published at https://doi.org/10.1007/978-3-540-70720-2_31
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