Paper: Clustering Semantic Spaces of Suicide Notes and Newsgroups Articles.

ACL ID W09-1323
Title Clustering Semantic Spaces of Suicide Notes and Newsgroups Articles.
Venue Workshop on Biomedical Natural Language Processing
Session
Year 2009
Authors
  • Pawel Matykiewicz (Cincinnati Children's Hospital Medical Center, Cincinnati OH; Nicolaus Copernicus University, Torun Poland)
  • Wlodzislaw Duch (Nicolaus Copernicus University, Torun Poland)
  • John P. Pestian (Cincinnati Children's Hospital Medical Center, Cincinnati OH)

Historically, suicide risk assessment has re- lied on question-and-answer type tools. These tools, built on psychometric advances, are widely used because of availability. Yet there is no known tool based on biologic and cogni- tive evidence. This absence often cause a vex- ing clinical problem for clinicians who ques- tion the value of the result as time passes. The purpose of this paper is to describe one exper- iment in a series of experiments to develop a tool that combines Biological Markers (Bm) with Thought Markers (Tm), and use machine learning to compute a real-time index for as- sessing the likelihood repeated suicide attempt in the next six-months. For this study we fo- cus using unsupervised machine learning to distinguish between actual suicide notes and newsgroups. This is im...