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NA HRANICÍCH UMĚNÍ, KREATIVITY A MÝTU. K PROBLEMATICE PREZENTAČNÍCH STRATEGIÍ SYNTETICKÝCH TEXTOVÝCH MÉDIÍ

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Piorecký K., Husárová Z.
Slovenská literatúra (Slovak Literature)
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2022
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vol. 69
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issue 5
499 – 514
EN
One of the aims of this study is to present foreign, Czech, and Slovak projects created by generating literary texts through the use of artificial neural networks (we propose the term synthetic textual media). However, the main goal is to provide a critical analysis of the presentation strategies applied in the publication and promotion of the results of these projects. We will therefore test the hypothesis that these modes of presentation lead to the mythicisation of artificial intelligence and inappropriately skew the share of human and non-human involvement in the production of generative texts. We understand synthetic textual media and their presentational para-texts in complementary textual relations, and stress the necessity of critically analysing them as a whole. This stems from the fact that the current practice of literature generated by artificial neural networks is not suitable for a close reading approach without reductive reception and (mis)interpretation. We are also aware of the specificity of the reception processes initiated by literary texts of this kind and strive to support the concept of literary metareading, which we consider more appropriate for the technological and literary levels of this type of text.
2

rofileSEEKER – system informatyczny wczesnego ostrzegania małych i średnich przedsiębiorstw przed bankructwem

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Burda A., Cudek P., Hippe Z. S.
Barometr Regionalny. Analizy i prognozy
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2012
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issue 3(29)
99-105
EN
This paper presents the construction of the ProfileSEEKER – the information system for early warning small and medium-sized enterprises from bankruptcy. The developed system is a set of five classifiers, using a variety of topologies of artificial neural net-works and Bayes belief network, supported by supervised machine learning methods. System performance was evaluated using the original validation, called queue validation procedure.
3

PREDICTION OF THE BANKRUPTCY OF SLOVAK COMPANIES USING NEURAL NETWORKS WITH SMOTE

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Tumpach M., Surovičová A., Juhászová Z., Marci A., Kubaščíková Z.
Ekonomický časopis (Journal of Economics)
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2020
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vol. 68
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issue 10
1021 – 1039
EN
Although the bankruptcy prediction models can be a stabilizing element on both macro and microeconomic levels, they are rather a domain of academic research than an instrument, widely applied in a business practice. It is especially true if the models are reflecting the conditions of countries of their origin, rather than countries of their intended uses. Besides, few of the models contain inherent flaws, including the absence of a methodical approach addressing this problem of the severely imbalanced representation of bankrupt companies in financial datasets. The article is focused on the use of oversampling with SMOTE (Synthetic Minority Oversampling Technique) algorithm under the condition of extremely imbalanced data sets of Slovak companies. While the model does not provide a single answer in many (if not most) of the situations, it still could be used for the selection of companies for which the more detailed (and expensive) analysis is not required.
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