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Knowledge Extraction from Artificial Associative Memory for Helping Senile Dementia Patients

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3316))

Abstract

We designed Knowledge Extraction mechanism from Artificial associative memory system for helping memory formation and associative knowledge retrieval of Senile dementia patients. This system has the hierarchical structure. It can learn and perceive the things and has the associative knowledge retrieval function according to the associative keywords. This system has also Episode memory described by Script which is helpful for the simple association of events. We constructed event oriented virtual memory and tested learning and associative knowledge retrieval function with a Senile dementia patient’s data.

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References

  1. Shim, J.: Knowledge retrieval using bayesian associative relation in the three dimensional modular system. In: Yu, J.X., Lin, X., Lu, H., Zhang, Y. (eds.) APWeb 2004. LNCS, vol. 3007, pp. 630–635. Springer, Heidelberg (2004)

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  2. Anderson, J.R.: Learning and Memory. Prentice Hall, Englewood Cliffs

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  3. Fausett, L.: Fundamentals of Neural Networks. Prentice Hall, Englewood Cliffs

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© 2004 Springer-Verlag Berlin Heidelberg

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Shim, J. (2004). Knowledge Extraction from Artificial Associative Memory for Helping Senile Dementia Patients. In: Pal, N.R., Kasabov, N., Mudi, R.K., Pal, S., Parui, S.K. (eds) Neural Information Processing. ICONIP 2004. Lecture Notes in Computer Science, vol 3316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30499-9_64

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  • DOI: https://doi.org/10.1007/978-3-540-30499-9_64

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23931-4

  • Online ISBN: 978-3-540-30499-9

  • eBook Packages: Springer Book Archive

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