Stalker: overcoming linguistic barriers in open source intelligence

The revolution in information technology is making open sources more accessible, ubiquitous and valuable. The international intelligence communities have seen open sources become increasingly easier and cheaper to acquire in recent years. But up to 80% of electronic data is textual and most valuable information is often hidden and encoded in pages which are neither structured nor classified. The process of accessing all these raw data, heterogeneous in terms of source and language, and transforming them into information is therefore strongly linked to automatic textual analysis and synthesis, which are greatly related to the ability to master the problems of multilinguality. This paper describes a content-enabling system that provides deep semantic search and information access to large quantities of distributed multimedia data for both experts and the general public. Stalker provides a language-independent search and dynamic classification features for a broad range of data collected from several sources in a number of culturally diverse languages.