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Semantic analysis processes are used for designing automatic data analysis sys-
tems, among which cognitive systems represent an important class.
Semantic analysis is the key to the correct operation of cognitive data analysis
systems. When this analysis is conducted, several different (but equally important
for the analysis) processes occur: the interpretation, the description, the analysis
and reasoning.
The main stages of semantic analysis are as follows:
data pre-processing:
filtration and segmentation;
approximation;
coding;
data representation:
recognising picture primitives;
identifying relations between picture primitives;
defining relations between objects in the image;
linguistic perception;
syntactic analysis;
pattern classification;
data classification;
feedback;
cognitive resonance;
data understanding.
The main stages of semantic analysis are shown in Figure 2.13.
A clear majority of the above semantic analysis stages deals with the data un-
derstanding process, since beginning with the syntactic analysis conducted using
the formal grammar defined in the system, there are stages aimed at identifying
the analysed data with particular focus on its semantics (the meaning it contains).
The stages of recognition itself become the starting point for further stages, re-
ferred to as the cognitive analysis. This is why the understanding process as such
requires the application of feedback during which the features of the analysed data
are compared to expectations which the system has generated from its expert
knowledge base. This feedback is called the cognitive resonance. It identifies
those feedbacks which turn out to be material for the analysis conducted, i.e. in
which features are consistent with expectations. The next element necessary is the
data understanding as such, during which the significance of the analysed changes
for their further growth or atrophy (as in lesions visible in medical diagnostic
images) is determined.
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