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Assessing the Similarity of Situations and Developments by Using Metrics

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Intelligent Decision Technologies 2017 (IDT 2017)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 72))

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Abstract

In this article we observe numerical evaluations of situations and developments. Similarities will be elaborated from structural and descriptive aspects. The basis of the structural similarity is homomorphism of algebraic systems. The bases of descriptive similarities are claims in descriptions of situations, which are expressible with formulas of calculations of the predictions. Developments will be addressed by binary precedency and sequential links. Mentioned connections will be observed as sets, elements of which are ordered pairs of situations. The procedure for numeric evaluation of similarities is based on metrics of relative difference of final sets. The numeric rating of similarity will be associated with plausibility: the more similar or close the objects are, the more plausible it is, that the acquired knowledge about one object will be valid for other similar object. The method of numeric evaluation of similarities may have interesting and beneficial implementation options for many areas.

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Author information

Authors and Affiliations

  1. Department of Information Technology, Estonian Business School, Tallinn, Estonia

    Peeter Lorents, Erika Matsak, Ahto Kuuseok & Daniil Harik

Authors
  1. Peeter Lorents
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  2. Erika Matsak
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  3. Ahto Kuuseok
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  4. Daniil Harik
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Corresponding author

Correspondence to Ahto Kuuseok .

Editor information

Editors and Affiliations

  1. Maritime University , Gdynia, Poland

    Ireneusz Czarnowski

  2. Bournemouth University and KES International, Poole, Dorset, United Kingdom

    Robert J. Howlett

  3. University of Canberra, Canberra, Aust Capital Terr, Australia

    Lakhmi C. Jain

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Lorents, P., Matsak, E., Kuuseok, A., Harik, D. (2018). Assessing the Similarity of Situations and Developments by Using Metrics. In: Czarnowski, I., Howlett, R., Jain, L. (eds) Intelligent Decision Technologies 2017. IDT 2017. Smart Innovation, Systems and Technologies, vol 72. Springer, Cham. https://doi.org/10.1007/978-3-319-59421-7_17

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  • DOI: https://doi.org/10.1007/978-3-319-59421-7_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59420-0

  • Online ISBN: 978-3-319-59421-7

  • eBook Packages: EngineeringEngineering (R0)

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