Citation

Perner P, Poelmans J, Elzinga P, Viaene S, Dedene G. Lect. Notes Comput. Sci. 2009; 5633: 247-260.

Copyright

(Copyright © 2009, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/978-3-642-03067-3_20

PMID

unavailable

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.