The objective of this research project is to develop a software toolset that mines a large set of unstructured text archives of human rights abuses. The software tool is designed to discover stories of hidden human rights victims and unidentified perpetrators. These stories do not exist in one document, but as fragments of text embedded across multiple documents. Thus, these stories can be identified only when reading across a large number of related documents. The current approach of manually reading to identify such stories is extremely tedious, time consuming, unsystematic, and error-prone. Human readers find it difficult to correlate the identity of victims, perpetrators, and details of abuse that reside across multiple documents. Thus, success of this project has large implications for the human rights community, as currently there is a lack of adequate tool support for automatically reading and identifying stories from large-scale unstructured text document sets.
Karthikeyan Umapathy, technical advisor, is associate professor of Information Systems at UNF. His research focuses on the design and development of complex information systems, the analysis of web service standards, and the empirical investigation of the processes through which IT standards are developed. In his teaching, he seeks to create real–world service learning opportunities for his students beyond the classroom.