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Artificial Intelligence

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Artificial Intelligence for Business Analytics

Abstract

McCarthy defines artificial intelligence as “[…] the science and technology of creating intelligent machines, especially intelligent computer programs”. The discipline is related to the task of using computers to understand human intelligence. Thus, many subfields and methods of AI also rely on biological patterns and processes but AI is not limited to these biologically observable methods.

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Notes

  1. 1.

    See the execution of Alan Turing in this regard. The mathematician and computer scientist is considered one of the most influential theorists of early computer development and computer science.

  2. 2.

    However, it must be said that this classification is not uncontroversial.

  3. 3.

    Mostly mathematical optimization systems are meant here.

  4. 4.

    Further information can be found in [2].

  5. 5.

    The curse of dimensionality refers to several phenomena that occur when analyzing and organizing data in high-dimensional spaces (often with hundreds or thousands of dimensions) that do not occur in low-dimensional environments, such as the three-dimensional physical space of everyday experience. The common theme of these problems is that as the dimensionality increases, the volume of the space increases so rapidly that the available data becomes sparse. In machine learning problems where learning is done from a limited number of data samples in a high dimensional feature space, where each feature has a set of possible values, an enormous amount of training data is usually required to ensure that there are multiple samples with each combination of values. More information on the curse and possible solutions can be found, for example, in [4].

  6. 6.

    For more detailed information on this learning model, see [5] or [6].

  7. 7.

    For further information see [8] or [9].

  8. 8.

    A survey of the various developments around the Apriori algorithm can be found in [13] or [14].

  9. 9.

    See [14] or [16].

  10. 10.

    For a comprehensive and scientifically sound presentation of second-order algorithms, see the University of Standford Lecture Notes by Prof. Ye. Available here: https://web.stanford.edu/class/msande311/lecture13.pdf.

  11. 11.

    See: [24].

  12. 12.

    See: [25].

  13. 13.

    See: [26].

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Authors and Affiliations

  1. Chair of Business Informatics and Integrated Information Systems, University of Duisburg-Essen, Essen, Germany

    Felix Weber

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  1. Felix Weber
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Weber, F. (2023). Artificial Intelligence. In: Artificial Intelligence for Business Analytics. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-37599-7_2

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  • DOI: https://doi.org/10.1007/978-3-658-37599-7_2

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