A case of using formal concept analysis in combination with emergent self organizing maps for detecting domestic violence

Authors
Publication date 2009
Host editors
  • P. Perner
Book title Advances in Data Mining : Applications and Theoretical Aspects
Book subtitle 9th industrial conference, ICDM 2009, Leipzig, Germany, July 20-22, 2009 : proceedings
ISBN
  • 9783642030666
ISBN (electronic)
  • 9783642030673
Series Lecture Notes in Computer Science
Event 9th Industrial Conference on Data Mining (ICDM 2009), Leipzig, Germany
Pages (from-to) 247-260
Publisher Berlin: Springer
Organisations
  • Faculty of Economics and Business (FEB) - Amsterdam Business School Research Institute (ABS-RI)
Abstract
In this paper, we propose a framework for iterative knowledge discovery from unstructured text using Formal Concept Analysis and Emergent Self Organizing Maps. We apply the framework to a real life case study using data from the Amsterdam-Amstelland police. The case zooms in on the problem of distilling concepts for domestic violence from the unstructured text in police reports. Our human-centered framework facilitates the exploration of the data and allows for an efficient incorporation of prior expert knowledge to steer the discovery process. This exploration resulted in the discovery of faulty case labellings, common classification errors made by police officers, confusing situations, missing values in police reports, etc. The framework was also used for iteratively expanding a domain-specific thesaurus. Furthermore, we showed how the presented method was used to develop a highly accurate and comprehensible classification model that automatically assigns a domestic or non-domestic violence label to police reports.
Document type Conference contribution
Language English
Published at https://doi.org/10.1007/978-3-642-03067-3_20
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