SBIR-STTR Award

Automated extraction of event location information enables intelligence analysts to rapidly visualize information contained in large volumes of unstructured textual data. Although natural language text analysis software already has the ability to extract locations to some degree, there still exist deficiencies that we will address in this project. We will expand geocoding to include facilities rather than only geocoding locations. Linking location mentions with event mentions or each other has not received an adequate treatment in existing literature. We will address this issue by implementing and benchmarking modules for these tasks. We will also study the prospect of automated extraction of implicit location-event extraction, namely determining the location of an event mentioned in an input sentence even if that location is not explicitly mentioned there.

Benefit:
The main anticipated benefit of this work involves advancements in methods to automatically extract and geocode locations corresponding to events as they occur in unstructured data. These are especially useful in enhancing event visualization from such data. Some of the methods to be studied involve extracting information that is only implicitly mentioned in the text, which is one step beyond what most systems can produce.

Keywords:
Information Extraction, Geo-Coding, Location-Stamping, Geo-Parsing, Geospatial Analytics

Large volumes of unstructured data are generated daily, which cause information overload for analysts who must sift through the data. A system that is able to automatically plot all of the events occurring in that data on a map would be of great value to these analysts. The proposed system conducts research and development in various aspects of text analytics technology in order to perform this task more thoroughly and accurately. This includes increasing the accuracy of detecting place names as well as geocoding them. It also includes parsing of relative location expressions (``three miles west,'' ``between Mosul and Tikrit''), linking events and their corresponding locations appearing in the same sentence, and determining the location of an event when its location is not explicitly mentioned in the same sentence.

Benefit:
The main anticipated benefit of this work involves working software that automatically extracts and geocodes locations corresponding to events as they occur in unstructured data. These are especially useful in enhancing event visualization from such data. In addition, the proposed software should be able to extract information that is only implicitly mentioned in the text, which is one step beyond what most systems can produce.

Keywords:
Information Extraction, Geo-Coding, Location-Stamping, Geo-Parsing, Geospatial Analytics