Structured Knowledge Space
Abstract
Structured Knowledge Space (SKS) is an end-to-end software system developed to solve a problem that has frustrated national security decision makers: "How do we take advantage of the enormous amounts of information communicated daily through a wide variety of reporting venues?" SKS combines open-source technologies (e.g., Java and Lucene), custom-built software, and domain knowledge about important entities in intelligence reporting to create a robust system that facilitates searching over a document collection that had previously been largely unsearchable. SKS builds searchable archives of text-based intelligence reports, extracts information from free-form documents, and makes the information discoverable through a keyword and faceted-search interface. SKS's tools include ones that search for approximate name matches or geographic locations referenced in text. SKS's modern tiered architecture scales to significant data storage and retrieval demands. SKS exploits modern natural language processing and information retrieval techniques to improve the ability to search, analyze, and effectively utilize intelligence reports and the valuable information that they contain. Its functionality is similar to niche capabilities in other industries, e.g., Google News for aggregating news sources and Radian6 for social media analysis. However, SKS was designed to meet the specific needs of the military and intelligence communities.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 01, 2013
- Accession Number
- ADA594043
Entities
People
- Delsey Sherrill
Organizations
- Massachusetts Institute of Technology