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Associative Historical Knowledge Extraction from the Structured Memory

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Rough Sets and Current Trends in Computing (RSCTC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3066))

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Abstract

For the intelligent automatic information processing, the efficient memory structure and intelligent knowledge extraction mechanism using this structure should be studied. Accordingly, we propose structured memory with the mechanism for extracting the historical knowledge. In a retrieval stage, the empirical historic factor effects on the reaction of a certain class. This system is applied to the area for estimating the purchasing degree from the type of customer’s tastes, the pattern of commodities and the evaluation of a company.

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Author information

Authors and Affiliations

  1. Division of General Studies, Computer Science, Kangnam University, San 6-2, Kugal-ri, Kihung-up, YongIn Si, KyeongKi Do, Korea

    JeongYon Shim

Authors
  1. JeongYon Shim
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Editor information

Editors and Affiliations

  1. Shimane University, 89-1 Enya-cho Izumo, 6938501, Shimane, Japan

    Shusaku Tsumoto

  2. Systems Research Institute, Polish Academy of Sciences, 01-447, Warsaw, Poland

    Roman Słowiński

  3. The Linnaeus Centre for Bioinformatics, Uppsala University, Uppsala, Sweden

    Jan Komorowski

  4. Institute of Computer Science, Polish Academy of Sciences, 01–237, Warsaw, Poland

    Jerzy W. Grzymała-Busse

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© 2004 Springer-Verlag Berlin Heidelberg

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Shim, J. (2004). Associative Historical Knowledge Extraction from the Structured Memory. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds) Rough Sets and Current Trends in Computing. RSCTC 2004. Lecture Notes in Computer Science(), vol 3066. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25929-9_68

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  • DOI: https://doi.org/10.1007/978-3-540-25929-9_68

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22117-3

  • Online ISBN: 978-3-540-25929-9

  • eBook Packages: Springer Book Archive

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