Using the Levenshtein algorithm for the categorization of information systems users

Authors

DOI:

https://doi.org/10.18372/2073-4751.79.19366

Keywords:

Levenshtein distance, user categorization, adaptive systems, user behavior, sequence similarity

Abstract

The study is devoted to the application of the Levenshtein distance algorithm to categorize users based on behavior in information systems, with an emphasis on dynamic adaptation in e-learning environments. The experiment used data from the MS SQL Server online course and the hardware and software complex for teaching the Braille font, which allows you to switch the content based on scenarios that correspond to the category of users. The results show the effectiveness of using the Levenshtein distance algorithm for user categorization and training has maintained a positive trend of advancement according to predefined training scenarios. The study also highlights the potential of adaptive e-learning systems to improve learning outcomes by adapting content to the individual needs of users.

References

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Published

2024-11-04

Issue

Section

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