Graphical methods for real-time fusion and estimation with soft message data

Fusion of observational data acquired by human observers and couched in linguistic form is a modern-day challenge for the fusion community. This paper describes a basic research effort examining various strategies for associating and exploiting such data for intelligence analysis purposes. An overall approach is described that involves Latent Semantic Analysis, Inexact Graph Matching, formal ontology development, and Social Network Analyses. Not all the methods have yet been employed but the exploitation of the developed ontology and graphical techniques have been implemented in a working prototype and preliminary results have shown promise. Planned future research will complete the implementation of the methods described herein and add yet further enhancements.