Research on Natural Language Processing Problems Based on LSTM Algorithm

B. Hu
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引用次数: 1

Abstract

In the process of the development of modern society, the network text analysis system is more and more important, and the research in the field of natural language processing has been comprehensively developed. In this research process, the natural language processing system mainly uses deep learning technology to realize deep learning technology, mainly through different neural networks to complete model construction, based on language analysis, using word segmentation and sentence classification methods. The long sentences are processed to ensure that the computer can better understand the text semantics of the system. Based on the above background, this paper designs a natural language analysis system to judge the word order and semantics of language characters conduct deep mining of language features based on neural networks. And simultaneously classify data mining results.
基于LSTM算法的自然语言处理问题研究
在现代社会的发展过程中,网络文本分析系统越来越重要,自然语言处理领域的研究也得到了全面的发展。在本研究过程中,自然语言处理系统主要采用深度学习技术来实现深度学习技术,主要通过不同的神经网络来完成模型构建,在语言分析的基础上,采用分词和句子分类的方法。对长句子进行处理,以确保计算机能够更好地理解系统的文本语义。基于以上背景,本文设计了一个自然语言分析系统,对语言字符的词序和语义进行判断,并基于神经网络对语言特征进行深度挖掘。同时对数据挖掘结果进行分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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