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Research of heuristic approaches for determining the tonality of text messages in natural language processing problems

机译:在自然语言处理问题中确定文本消息色调的启发式方法研究

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Determining the tonality of the text is a difficult task, the solution of which essentially depends on the context, the field of study and the amount of text data. The analysis shows that the authors in their works do not jointly use the full range of possible transformations on the data and their combinations. The article explores a generalized approach, which consists in sequentially passing through the stages of intelligence analysis, obtaining a basic solution, vectorization, preprocessing, tuning hyperparameters and modeling. The experiments carried out by iterative application of these stages give a positive increase in quality for classical machine learning algorithms and a significant increase for deep learning.
机译:确定文本的音调是一项艰巨的任务,其解决方案基本上取决于上下文,研究领域和文本数据量。分析表明,作者在其作业中没有共同使用数据和它们组合的全方位。该文章探讨了一种广义方法,它包括依次通过智能分析的阶段,获得基本解决方案,矢量化,预处理,调整超参数和建模。通过迭代应用这些阶段进行的实验使古典机器学习算法和深度学习的显着增加,质量增加了质量。

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