项目管理中的多模态数据分析:使用机器学习的前景

P. Mikhnenko
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引用次数: 0

摘要

现代项目环境的特点是高度复杂性、不确定性、变化的速度和深度,这些都会在项目生命周期内对项目产生影响。然而,项目的变更管理流程并没有考虑到实施动态处理多模态数据阵列的分析程序的必要性。本研究的目的是确定项目管理分析程序的内容,并证明使用机器学习技术可有效实施这些程序。方法论基础是项目管理方法、变革理论、人工智能和机器学习的概念以及分析方法。工作中还使用了项目管理过程的描述性建模方法和专家对机器学习技术使用前景的评估方法。信息库由有关研究主题的科学资料和专家评估组成。研究结果使我们得出结论,在多模态数据分析方面,自然语言处理和智能决策支持技术最受欢迎,可作为项目管理领域新技术解决方案的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of Multimodal Data in Project Management: Prospects for Using Machine Learning
The modern project environment is characterized by high complexity, uncertainty, speed and depth of changes that affect the project during its life cycle. However, the project’s change management processes do not take into account the need to implement analytical procedures for dynamic processing of multimodal data arrays. The purpose of the study is to determine the content of analytical procedures for project management and substantiate the use of machine learning technologies for their effective implementation. The methodological basis was project management methods, theory of change, concepts of artificial intelligence and machine learning, as well as analytical approaches. Methods of descriptive modeling of the project management process and expert assessments of the prospects for using machine learning technologies were also used in the work. The information base was made up of scientific materials on the topic under consideration, as well as expert assessments. The results of the study allowed us to conclude that for the analysis of multimodal data, natural language processing and intellectual decision support technologies are most in demand, which can serve as the basis for new technological solutions in the field of project management.
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