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Data management in cognitive financial systems

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  • Ogiela, Lidia

Abstract

This publication discusses ways of using cognitive analyses for semantically interpreting economic figures. A semantic analysis making use of mathematical linguistic algorithms in order to extract meaning from sets of analysed data is illustrated with an example of a class of cognitive systems designed to analyse economic figures, or more precisely, financial ratios. The cognitive analysis systems presented in this publication are discussed as exemplified by the class of Cognitive Financial Analysis Information Systems (CFAIS). This publication proposes algorithms executed by a broad class of automatic data interpretation and understanding systems designed for the in-depth semantic analysis and interpretation of the results obtained. This will be done by defining new system classes as applications supporting decision-making processes, useful in various areas of knowledge.

Suggested Citation

  • Ogiela, Lidia, 2013. "Data management in cognitive financial systems," International Journal of Information Management, Elsevier, vol. 33(2), pages 263-270.
    • Handle: RePEc:eee:ininma:v:33:y:2013:i:2:p:263-270
    DOI: 10.1016/j.ijinfomgt.2012.11.008
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    References listed on IDEAS

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    1. Buchanan, Steven & McMenemy, David, 2012. "Digital service analysis and design: The role of process modelling," International Journal of Information Management, Elsevier, vol. 32(3), pages 251-256.
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    Cited by:

    1. Ogiela, Lidia & Ogiela, Marek R., 2014. "Cognitive systems for intelligent business information management in cognitive economy," International Journal of Information Management, Elsevier, vol. 34(6), pages 751-760.
    2. Ogiela, Lidia, 2015. "Advanced techniques for knowledge management and access to strategic information," International Journal of Information Management, Elsevier, vol. 35(2), pages 154-159.
    3. Hachaj, Tomasz & Baraniewicz, Danuta, 2015. "Knowledge Bricks—Educational immersive reality environment," International Journal of Information Management, Elsevier, vol. 35(3), pages 396-406.

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