Using text mining and machine learning for detection of child abuse
Date
2016
Journal Title
Journal ISSN
Volume Title
Publisher
arXiv
Abstract
Abuse in any form is a grave threat to a child's health. Public health institutions in the Netherlands try to identify and prevent different kinds of abuse, and building a decision support system can help such institutions achieve this goal. Such decision support relies on the analysis of relevant child health data. A significant part of the medical data that the institutions have on children is unstructured, and in the form of free text notes. In this research, we employ machine learning and text mining techniques to detect patterns of possible child abuse in the data. The resulting model achieves a high score in classifying cases of possible abuse. We then describe our implementation of the decision support API at a municipality in the Netherlands. (Author Abstract)
Description
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Article
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Keywords
child abuse, prevention, intervention, International Resources, Netherlands, internet, cybercrime
Citation
Amrit, C., Paauw, T., Aly, R., & Lavric, M. (2016). Using text mining and machine learning for detection of child abuse. arXiv preprint arXiv:1611.03660.