SBIR-STTR Award

The ultimate aim of this project is to enable better entity-oriented situation awareness systems to be developed. Such systems should enable operators to rapidly “connect the dots” and allow them to track entities of interest. In this Phase I project we will design an approach for collecting information about entities from multiple heterogeneous sources, and for consolidating that information into entity profiles. We will also develop technology that will enable profiles to be monitored, so that alerts can be generated when significant changes occur. The project will explore the application of the technology, including an application to streamline the Market Research and Source Selection Phases of the Air Force’s acquisition cycle.

Benefit:
To achieve significant improvement in situation awareness applications, we need easy-to-use systems that enable information to be integrated and monitored, without necessitating a long, arduous, expensive programming project for each application that is created. The research described here will develop such an approach for collecting, integrating and monitoring information about entities. The work has a very targeted application for the military, which is to streamline the Market Research and Source Selection Phases of the Air Force’s acquisition cycle. In addition, there are important commercial markets for the technology. One market is the background screening industry. Currently, background checks on both companies and individuals tend to be a done sporadically, but in many situations, monitoring relevant information sources would be highly preferred. This technology improvements that we propose to investigate will enable such applications to be developed.

Keywords:
Information Integration, Artificial Intelligence, Machine Learning, Information Extraction, Entity-Oriented Data Integration

The ultimate aim of this project is to enable better entity-oriented situation awareness systems to be developed. Such systems should enable operators to rapidly “connect the dots” and allow them to track entities of interest. In this Phase II project we will implement an approach for collecting information about entities from multiple heterogeneous sources, and for consolidating that information into entity profiles. The resulting system, EMonitor, will enable profiles to be monitored, so that alerts can be generated when significant changes occur. The project will explore the application of the technology, including an application to streamline the Market Research and Source Selection Phases of the Air Force’s acquisition cycle, as well as an application that will help intelligence analysts monitor open source data.

Benefit:
To achieve significant improvement in situation awareness applications, we need easy-to-use systems that enable information to be integrated and monitored, without necessitating a long, arduous, expensive programming project for each application that is created. The research described here will develop such an approach for collecting, integrating and monitoring information about entities. The work has multiple applications for the Air Force, such as streamlining the Market Research and Source Selection Phases of the Air Force’s acquisition cycle. In addition, there are important commercial markets for the technology. One market is the background search industry. Currently, background checks on both companies and individuals tend to be a done sporadically, but in many situations, monitoring relevant information sources would be highly preferred. The technology prototyped in this project will enable such applications to be developed.

Keywords:
Information Integration, Information Aggregation, Artificial Intelligence, Entity Resolution, Monitoring And Alerting