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phenomenon, this knowledge, which has not been collected in the system (be-
cause the knowledge could not be accessed), should not be considered secret.
In the case of UBPAS systems, just like other classes of cognitive categorisa-
tion systems, we cannot accept the thesis of the complete separation of overt and
secret knowledge. It should be emphasised that bases of overt knowledge defi-
nitely dominate in these systems, but we cannot completely rule out some contri-
bution of secret knowledge when the knowledge bases are built by expert teams.
This approach to public knowledge means that we can agree with Cleeremans
[23], that knowledge is secret when it influences the processing, interpretation and
analysis of information without being aware of its features. Regardless of the un-
awareness of its impact on analysis processes, secret knowledge is represented in
the memory of UBPAS systems, so it can be retrieved from it and used in analysis,
interpretation and reasoning processes.
The next class of UBCCS subsystems are UBSAS systems used for varied sig-
nal analysis, and UBACS systems which are automatic control systems. These two
types of systems are only mentioned in this study, as their role and significance
has been described in various scientific and research publications by other re-
searchers [3], [28], [54], [58], [118], [146], [148], [153], [157], [159].
Apart from the UBDSS, UBMSS and UBPAS systems presented above, this
book will propose UBIAS cognitive systems designed for analysing image-type
data and used to analyse various types of image patterns, in particular medical im-
ages [87]-[89], [95]-[109]. UBIAS systems are the fruit of several years of the au-
thors' research and their characteristics are the leading subject of chapter 5, where
they will be discussed in greater depth.
All the types of cognitive categorisation systems presented before have wide-
ranging applications, from economics, sociology and philosophy to technical and
defence sciences, medicine or natural science.
All cognitive categorisation system types use methods of cognitive analysis in
their operation to extend the capabilities of classical data analysis technologies
in order to reason based on the semantics (meaning) of that data or the analysed
information.
3.2 A Formal Perspective on Cognitive Categorisation Systems
Both the ongoing scientific research work and the rapid development of informa-
tion systems allow a new class of systems - cognitive categorisation systems - to
be introduced for analysing and interpreting data.
In this study, the authors propose the following definition of computerized cog-
nitive categorisation.
'Cognitive categorisation systems' describe intelligent information systems de-
signed for conducting in-depth data analyses based on the semantic contents of
this data. Semantic analyses are conducted with algorithms for describing this data
