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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 15 Issue 5, 2024.
Abstract: Analysis of trends in the development of emerging technologies based on patents is a well-recognized approach. An increase in the number of patents precedes the extensive spread of technological solutions and their incorporation in production and professional activities, making it possible to perform predictive analysis. The field of digital technology, which is changing most dynamically among production areas, was chosen as the object of study. The study develops an approach to the analysis of emerging technologies that are related to a given domain. Methods for obtaining quantitative parameters have been developed based on time series representing the number of patents per year. The concept of a parameter plane has been introduced. It includes the parameters of stable growth/decline and annual quantity of patents. A special feature of the approach is the calculation of parameters for the last observed segment of the stable dynamic behavior of the time series based on the developed algorithm. The work takes the Digital Marketing domain as an example and presents analysis of 296 keywords related to this concept. Based on time series constructed from the patent database for 2000-2021, the most promising technologies were identified. The application of the results for the generation of topical educational content in the Digital Marketing field is considered.
Evgeny Nikulchev and Dmitry Ilin, “Generation of Topical Educational Content by Estimation of the Number of Patents in the Digital Field” International Journal of Advanced Computer Science and Applications(IJACSA), 15(5), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0150575
@article{Nikulchev2024,
title = {Generation of Topical Educational Content by Estimation of the Number of Patents in the Digital Field},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0150575},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0150575},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {5},
author = {Evgeny Nikulchev and Dmitry Ilin}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.