Military Communications and Information Technology: A Trusted ...

270 Military Communications and Information Technology...
There are various NLP technologies that can support intelligence with the processing
of text. A selection of those is presented below:
• Information retrieval (IR): Information retrieval is the technology underlying
modern search engines, i.e., it is concerned with efficiently and effectively
searching for documents. By the application of professional search methods
we are able to find specific texts from document collections like databases
or the World Wide Web.
• Document classification: Document classification (or text categorization)
is an NLP method to assign documents to one or more classes or categories.
This may also mean the classification of documents relevance. As document
classification is usually used to enhance information retrieval, it is
sometimes regarded as a sub-field of IR.
• Information extraction (IE): Information extraction describes the extraction
of specifically defined information from text. For this, different text
processing is performed. Critical information is identified and extracted
and may also be structured and combined.
• Text mining: Text mining refers to the process of deriving text content. The aim
is to discover previously unknown information that is relevant for a particular
purpose. In the course of text mining different NLP technology may be applied
such as, for example, the related task of IE to extract specific items.
• Opinion mining: Opinion mining, which is also called sentiment analysis,
involves the analysis of subjective information from text. It is used to try to
determine the attitude of a writer with respect to some topic or the overall
contextual polarity of a document.
• Machine translation (MT): The automatic translation of text is done by
machine translation. There are different approaches to generate a target
language translation from a source language text. Which approach is best
depends on the application and various circumstances. Most modern research
is performed in the area of statistical machine translation (SMT).
In section 4, SMT is described in more detail.
The technologies presented can be applied to assist the human intelligence
analyst. Through automatic document processing, the intelligence process can be
improved in terms of efficiency as well as effectiveness. The computational processing
of text is much faster than human processing. This means that time-critical information
will reach the mission’s command and control in a much shorter time. Many
intelligence tasks cannot possibly be performed by humans (such as the manual
search for information in the web). Only by the use of technology are we able to
fully exploit the information that we have access to nowadays. In the following, we
illuminate one possible approach of supporting the intelligence process by the application
of NLP technology (Figure 2).
a) Collection: Intelligence involves the collection of data that are relevant for
the mission. There are different sources of relevant textual data. For example,