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Position Papers of the 18th Conference on Computer Science and Intelligence Systems

Annals of Computer Science and Information Systems, Volume 36

Evaluation of selected Cardinality Pattern functions and linguistic variables applied to authors dominant discipline classification

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DOI: http://dx.doi.org/10.15439/2023F2798

Citation: Position Papers of the 18th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 36, pages 111–117 ()

Full text

Abstract. The ongoing study aimed to investigate the impact of utilizing intelligent counting algorithms to determine the dominant discipline of authors. This paper addresses the issue of ambiguously assigning disciplines to authors, which has become a prevalent problem. The methodology section outlines the approach employed in this study, including the utilization of intelligent counting, cardinality pattern functions, and evaluation metrics. In the results section, we present the findings of the study, demonstrating that by employing specific Cardinality pattern functions and linguistic variables, we were able to achieve a return that surpassed the number of disciplines unambiguously determined for authors by up to 30\%, surpassing the results obtained using well-known methods.

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