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incomparably faster than a machine can. However, machine understanding techniques
are also improving, so in time they will be able to execute more complex reasoning by
referring to the meaning of the collected data, and not just executer simple analyses of
this data. Advanced artificial intelligence techniques are used to make information
systems capable of such semantic reasoning about data. Apart from the simple analy-
sis of information and the possible classification (recognition) of data identified for
analysing, these techniques also enable extracting significant semantic information
from this data, which indicates the interpretation of its meaning. At the present stage,
the semantic analysis of data is always rooted in some context assumed up front, as
the computer cannot at the same time discover the purpose of the analysis and its
result. This means that the cognitive systems being constructed are trying to under-
stand data and reason about it having the purpose of this reasoning specified. This
must be contrasted with a human, who encounters a specific novel situation, analyses
its many facets, and as a result can draw completely unexpected conclusions which
bear witness to the deep mental exploration of this situation, in other words to under-
standing it fully.
Acknowledgement
This work has been supported by the Ministry of Science and Higher Education,
Republic of Poland, under project number N N516 196537.
References
[1]
Albus, J.S., Meystel, A.M.: Engineering of Mind - An Introduction to the Science of In-
telligent Systems. A Wiley-Interscience Publication John Wiley & Sons Inc., Hoboken
(2001)
[2]
Berners-Lee, T.: Weaving the Web. Texere Publishing (2001)
[3]
Berners-Lee, T., Fensel, D., Hendler, J.A., Lieberman, H., Wahlster, W. (eds.): Spinning
the Semantic Web: Bringing the World Wide Web to Its Full Potential. The MIT Press,
Cambridge (2005)
[4]
Branquinho, J. (ed.): The Foundations of Cognitive Science. Clarendon Press, Oxford
(2001)
[5]
Brejl, M., Sonka, M.: Medical image segmentation: Automated design of border detec-
tion criteria from examples. Journal of Electronic Imaging 8(1), 54-64 (1999)
[6]
Burgener, F.A., Kormano, M.: Bone and Joint Disorders. Thieme, Stuttgart (1997)
[7]
Chomsky, N.: Language and Problems of Knowledge: The Managua Lectures. MIT
Press, Cambridge (1988)
[8]
Cohen, H., Lefebvre, C. (eds.): Handbook of Categorization in Cognitive Science. El-
sevier, The Netherlands (2005)
[9]
Davis, L.S. (ed.): Foundations of Image Understanding. Kluwer Academic Publishers,
Dordrecht (2001)
[10]
Duda, R.O., Hart, P.E., Stork, D.G.: Pattern Classification, 2nd edn. A Wiley-
Interscience Publication/John Wiley & Sons, Inc. (2001)
[11]
Jurek, J.: On the Linear Computational Complexity of the Parser for Quasi Context Sen-
sitive Languages. In: Pattern Recognition Letters, vol. 21, pp. 179-187. Elsevier,
Amsterdam (2000)
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