Specificity and merging challenges in soft data association

This paper presents an initial system design approach for a data association process in the domain of counterinsurgency where multiple streaming soft (textual message) observation reports are a critical input to the process. An overview of the system includes processes from intelligent input control of soft data to the formation of associated, merged messages that are based on a methodology employing a graph-based approach. In addition to the baseline architecture, design tradeoff issues regarding the association process, to include the level of specificity with which the input is addressed, and optional techniques for associated-message merging, were explored. Applying data association to a counterinsurgency problem can potentially produce an improved comprehensive evidence base that will assist in reducing search time for subsequent discovery and inferencing operations and provide more accurate results for analysts making real time decisions.