使用深度学习从文本文档中识别相关文本

P. Parvathi, T. S. Jyothis
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引用次数: 4

摘要

如今,网络上可用的信息量是巨大的,并以指数级的速度增长。因此,从文本文档中识别相关文本就变得至关重要。文本分类是将文档归入预定义的类别的任务。有几种方法可以识别文本文档中哪些单词对于解释它所关联的类别是重要的。该方法采用深度学习卷积神经网络。并利用深度学习对分类进行准确预测。因此,通过F1 Score计算测试的精度,我们得到一个近似等于1的精度值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying Relevant Text from Text Document Using Deep Learning
Now-a-days the amount of information available on the web is enormous and incrementing at an exponential rate. Thus identifying relevant text from text document has become very crucial. Text classification is the task of relegating a document under a predefined category. There are several methods to identify which words in text documents are important to explain the category it is associated with. The proposed approach uses convolution neural network with deep learning. And the deep learning is used to predict the categories accurately. Thus by calculating the test’s accuracy by F1 Score, we get an accuracy value which is approximately equal to 1.
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