Leadership Agent for Multi-source Information Fusion in Counter-Terrorism

Current document search techniques are inadequate to handle queries whose answer requires establishing links among a number of (potentially obscure) facts. We propose to remedy this situation with a prototype system that applies statistical and knowledge-based methods to the problem of identifying chains of connections between terms and entities. We will extend existing predictive annotation methods for indexing entities by tagging them with Cyc concepts. In addition, our system will be capable of indexing entire facts, by applying Cyc's parsers to text sentences. Parsing a sentence into the CycL representation language results in a full semantic translation, so links among entities mentioned in a sentence will be transparent in the CycL representation. We propose also to demonstrate the discovery of "anonymous" links, by using technology we developed during the ARDA AQUAINT project. This module, the Holistic Query Expansion Algorithm (HQEA), is designed to process a textual query and produce a set of pairwise highly-correlated terms that connect all the terms within the original query into a coherent topic. Finally, a user-feedback mechanism will be developed to refine the performance of the Cyc-based semantic annotators.