Elevating Semantic Search by Marrying Social Network and Content Analysis Techniques

The military"s ability to exploit streams of heterogeneous information sources has not kept pace with the enterprise"s ability to generate them. In order to make substantial progress in enhancing the warfighters"situational awareness, new approaches are required to automatically link related information. We propose to develop this capability by tapping the synergy between existing text analysis and Social Network Analysis (SNA) techniques. Our overall approach can be viewed as"pearl-culturing", in which our system will first utilize an ensemble of existing text analytics tools to identify clusters of strongly related documents. These tools will include (among others) our own proven technology for identifying documents that were either derived from a common information source or provide details regarding the same event. Our system will then employ ontology-based extraction tools to extract entities and relations from these tight clusters (treating them as if they were a single document). This approach will allow us to utilize existing technology to create more complete entity profiles than has been previously possible. Finally, SNA metrics will be used to quantify and qualify the relationships among documents, entities, and concepts. Ultimately this technology will support improved semantic search as well as SNA across the enterprise.