基于自动机器学习的神经网络结构文本处理方法

Bowen Jing
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引用次数: 0

摘要

在社会经济和科技创新发展的今天,各个领域的信息处理速度越来越快,具有不同功能的管理系统,已经被引用到人们的日常生活和工作中,这也使得行业发展积累了丰富的数据资源。如何从海量文本数据中获取有价值的信息,是我国科研工作者讨论的主要问题。在了解结构化文本处理现状的基础上,本文提出了一种基于自动机器学习和神经网络算法的神经网络结构化文本处理方法。同时,以医学文本数据的结构化处理为例,讨论了该方法的应用优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural network structure text processing method based on automatic machine learning
In the social economy and technological innovation and development, the information process in all fields is getting faster and faster, the management system with different functions, has been cited to People's Daily life and work, which also makes the industry development has accumulated rich data resources. How to obtain valuable information in mass text data is the main problem discussed by Chinese scientific researchers. On the basis of understanding the status quo of structured text processing, this paper proposes a neural network structured text processing method based on automatic machine learning and neural network algorithm. At the same time, taking the structured processing of medical text data as an example, the application advantages of this method are discussed.
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