  We provide an overview of tools enabling users to utilize data from open
sources for decision-making support in weakly-structured subject domains.
Presently, it is impossible to replace expert data with data from open sources
in the process of decision-making. Although organization of expert sessions
requires much time and costs a lot, due to insufficient level of natural
language processing technology development, we still have to engage experts and
knowledge engineers in decision-making process. Information, obtained from
experts and open sources, is processed, aggregated, and used as basis of
recommendations, provided to decision-maker. As an example of a
weakly-structured domain, we consider information conflicts and operations. For
this domain we propose a hybrid decision support methodology, using data
provided by both experts and open sources. The methodology is based on
hierarchic decomposition of the main goal of an information operation. Using
the data obtained from experts and open sources, we build the knowledge base of
subject domain in the form of a weighted graph. It represents a hierarchy of
factors influencing the main goal. Besides intensity, the impact of each factor
is characterized by delay and duration. With these parameters taken into
account, main goal achievement degree is calculated, and changes of target
parameters of information operation object are monitored. In order to
illustrate the suggested hybrid approach, we consider a real-life example,
where we detect, monitor, and analyze actions intended to discredit the
National academy of sciences of Ukraine. For this purpose, we use specialized
decision-making support and content monitoring software.
