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Abstract <p>This article presents a decision support algorithm for the commercialization of intellectual property that integrates regression analysis and machine learning methods. The algorithm takes a range of factors into account, including patent features, market indicators, technological trends, and economic conditions. A&#xa0;formalized problem statement with an objective function for minimizing the mean square error is proposed, and the algorithm implementation stages are detailed: from data collection and preprocessing to the construction, validation, and dynamic updating of the predictive model. Particular attention is paid to the implementation of a dynamic assessment mechanism for technological trends to improve the model’s adaptability.</p>

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A Decision Support Algorithm for the Commercialization of Intellectual Property

  • 期刊论文

  • 发表日期：

    2026年2月1日

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  • S. I. Prudnikov,
  • E. Yu. Dorozhkin

摘要

Abstract

This article presents a decision support algorithm for the commercialization of intellectual property that integrates regression analysis and machine learning methods. The algorithm takes a range of factors into account, including patent features, market indicators, technological trends, and economic conditions. A formalized problem statement with an objective function for minimizing the mean square error is proposed, and the algorithm implementation stages are detailed: from data collection and preprocessing to the construction, validation, and dynamic updating of the predictive model. Particular attention is paid to the implementation of a dynamic assessment mechanism for technological trends to improve the model’s adaptability.