Exploit Unstructured Intelligence Sources
Find and correlate essential elements of information buried in structured and semi-structured intelligence products.
Supercharge the soft side of your analysis environment.
In irregular warfare, often the most valuable information for intelligence analysis is buried in unstructured, or soft, information sources. Modus Operandi’s Wave Exploitation Framework (Wave-EF) automatically identifies key concepts and relationships in unstructured data, tags them, and feeds them to analysts’ tools for correlation and visualization. Wave-EF frees analysts from tedious reading, markup and search tasks so that they focus on the big picture. By putting unstructured text on a par with more structured data, Wave-EF enables true all-source analysis.
Complex Concept Extraction
Wave-EF extracts 14 essential elements of information (EEIs):
persons, locations, communications, vehicles, organizations, groups, internet components, targets, activities, blue force, phone numbers, weapons, facilities, units, control measures.
Many basic text analytic tools concentrate on finding entities which are nouns. But that is not sufficient to extract the fundamental triad of intelligence fusion: Entity-Location-Time. Examples of this triad are when a High Value Individual was observed at a specific location and time, or a suicide bombing incident is planned to occur at a particular place and time.
Wave-EF takes extraction to the next level by treating these basic EEIs as concept building blocks. Relationship extractors tie concept building blocks together to describe more sophisticated constructs such as events. An IED incident, for example, is a type of event that can be linked to numerous concepts, such as multiple persons, organizations, locations, and times; to descriptive signature concepts such as detonation method, explosive type, and concealment method; and to effects such as destruction and casualties.
Content Enrichment with Semantic Tags
Content enrichment does for text what STP® Fuel Treatment does for gasoline—it makes the parts that consume it work more effectively. Content enrichment with semantic tags transforms unstructured text into content with meaning that both computers and humans can recognize. In a data mining scenario, these tags can be used by analysts to find specific intelligence products by searching for specific entities, for abstract concepts, or for relationships among entities that are contained within the product. In an alerting scenario, these tags can be examined by a semantic filter that determines whether the product is relevant to the analyst's expressed requirements. Get datasheet>>
Advanced Text Exploitation.
Wave is a government-off-the-shelf (GOTS) technology for intelligence applications that tackles the difficult problem of processing unstructured and semi-structured data.
The Wave-EF Cost and Time Advantage.
Wave solutions offer an alternative to traditional acquisition of custom software. By combining MO-developed GOTS and open source software, we bring our customers high quality, high capability solutions at a fraction of the traditional time and cost.
