This research effort begins with the analysis of a single document and extends the methodology into cross-document analysis, with the goal of providing an assortment of software tools for interactive discovery and directed query. The technology can also be used for computational preprocessing for corpus-based applications such as Spire. The current focus is to extend those techniques via improved mathematics and implementations, so as to work effectively on documents that are too large to be read in their entirety and too complex to be characterized as single points in topic space. A small part of this effort involves participation in workshops that will lead to the development of new metrics for dynamic analysis environments such as these. The current metrics of precision and recall are incomplete tools for assessing this new paradigm.
Queries are no longer the single centerpiece of the interaction.
The ability to identify and characterize areas of threat and vulnerability, and to manage and understand complex information in the area of defense, relies on the ability to understand an exponentially increasing base of textual information quickly without reading all of it. To this end, the use of wavelet-based document decomposition and novel visualization techniques will provide adjustable level of resolution summaries for single documents and cross document analysis. The task will also include participation in metric workshops to figure out how to measure the performance of such systems. The results of this research will be delivered as a prototype implementation.