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perspective theory [52]. The perspective theory is based on the framing effect, i.e.
the impact of the mental representation of the decision-making problem on the
content of decisions taken. The cognitive representation of a problem may change
completely or to a great extent as a result of the words used to describe it or of tak-
ing into account the broader context in which the decision is taken [87], [92]. A
person taking a decision compares to some extent by overlaying a kind of frame
on the considered situation, which leads to a specific presentation of the problem
and in consequence to taking a decision consistent with the framing process [77],
[87], [92].
The operation of cognitive decision systems depends on many significant com-
ponents of the human decision-making process. However, not all human aspects
of decision-making processes can be applied in systems without restrictions, be-
cause not all the rules mentioned constitute optimum decision-making rules. Cog-
nitive decision systems operate using significant elements of psychological theo-
ries transferred to the field of information systems. The cognitive decision-making
process itself is based on a complex human psychological process made up of
cognitive and motivational elements.
Cognitive categorisation systems, in addition to cognitive decision systems,
also include UBMSS information management systems built for taking strategic
decisions, for instance at enterprises. Information aspects play a significant role
and are quite important for cognitive systems of this type. These aspects do not
apply only to the information acquisition phase, but also to its correct processing
and interpretation. UBMSS systems, just as other classes of cognitive categorisa-
tion systems, work by using cognitive resonance, but their additional benefit is
that the cognitive system created within the information system is founded on the
semantic network found in the semantic network model. This is why in this type
of models the concepts connected with decision systems found in enterprises are
kept permanently in the form of a hierarchical network structure made up of nodes
and relations between them that link them. In particular nodes of the network,
various concept representations are coded, and in addition features characterising
these concepts are identified. These features are assigned to concept representa-
tions at the lowest possible level of the generality hierarchy. Introducing this type
of a concept representation meets the proposal of cognitive operation economy in
which the economy of the network structure can often be associated with the cost
of its operation. The analysis, interpretation and reasoning processes executed by
UBMSS systems facilitate the economical (from the financial point of view) use
of data contained in the available knowledge base in which concept representa-
tions are coded. In a UBMSS system, the semantic network described contains, in
addition to the concepts coded in the system and presented as network nodes, also
the semantic relations that link particular nodes. In this case, the semantic relation-
ship between the present concept representations is expressed as the sum of all
links between their designations and features. Concepts that are closely linked are
characterised by a value of their mutual links in the network, which value corre-
sponds to a certain community containing all their features. These links, called
network paths, are differentiated in the UBMSS system with regard to their
