Information Technology Reference
In-Depth Information
Chapter 8
Summary
Su m mar y
Cognitive informatics developed in the direction of broader and broader alliances
between technical computer science and cognitive science represents a very inter-
esting and promising field of science. Combining the whole range of solutions and
mechanisms that can be developed by cognitive science with computer science
opens wider and greater application opportunities. The solutions shown for prob-
lems presented herein also demonstrate further development opportunities for the
proposed solutions due to the constant development of cognitive informatics.
Cognitive data analysis and interpretation models make it possible to extract new,
extremely significant information - semantic information - from the analysed data
sets. It is this type of information which makes its deeper meaning-based interpreta-
tion possible. Semantic interpretation uncovers deep layers of information for the
person conducting the analysis process. They thus represent an extension of tradi-
tional data interpretation attempts whose end result was recognising the analysed ob-
ject, feature, information or data. Cognitive informatics based on semantic data in-
terpretation processes allows meaning to be extracted from sets of this data, which
meaning guides the automatic understanding process. This process is executed by
imitating human processes of perception, cognition, analysis and consequently, un-
derstanding, which can form the foundation for reasoning and projecting changes
that may occur in the future. Changes of the analysed phenomenon are an insepara-
ble element of cognitive data analysis processes, as the projection processes enable
the identification of possible improvements, or worse, deterioration. In cognitive
analysis of medical images of lesions, this type of projection is of great importance
for the patient's life and health. Similarly, conditions describing the economic stand-
ing of an enterprise or the financial premises for making a given investment are also
of great importance. They may not be about life and death, but for investors, finan-
cial advisors, economists and finally the economy they may bring a time of financial
downturn or prosperity. Cognitive solutions show how significant the stages of un-
derstanding the analysed data are. It is during this process that cognitive systems
take decisions to correctly classify the analysed situation and the consequences of its
occurrence, or if the analysed data is not understood, they attempt to include the new
solutions in the knowledge bases used for the cognitive data understanding process.
This stage, as an element of the system learning process, allows the system to con-
stantly improve and thus enables it to understand newer and newer situations.
Cognitive informatics is open to the semantic analysis of more than one type of
data. It has also offered opportunities for identification analyses, called the per-
sonalisation. Analysis methods based on cognitive and biometric mechanisms of
personal identification and verification made it possible to combine semantic in-
terpretation techniques with personal authentication and identification technolo-
gies. This combination gave birth to E-UBIAS systems which play a major role in
