Language & Semantic Systems
Understanding language, whether it is written, spoken, or implied by action, is an essential capability in many analytical systems. Central to understanding language in humans and machines are the areas of computational linguistics and formal semantic representation. Our work in computational linguistics is focused on building and integrating linguistic analysis components (such as named entity recognition, affect analysis, event recognition, word sense disambiguation, etc.) into analytical systems to aid in situational awareness. In addition to relying on existing software, we have significant research programs in frame analysis, sentiment detection, temporal reasoning, and participant profiling.
Formal representations of language data is necessary for complex reasoning tasks. Concepts like "semantic computing" and "semantic search" refer to computational techniques that use knowledge representation and deep linkage into the referents of information tokens in language (e.g., dictionaries, thesauri, ontologies) and in data resources (e.g., libraries, databases, and web-based repositories). Perhaps the best-known sense is in the "semantic web." Our work in this area ranges from infusion of taxonomy-based user interfaces, which help to guide the user through navigational tasks, to full-blown, ontology-based reasoning systems and the foundations of ontology technology. We work in domains ranging from biomedical to intelligence applications. We envision that semantic technologies could be applied in fields as diverse as intelligence analysis, data visualization, engineering simulation and modeling, and navigating environmental information.