Automatic composition classification method for primary school based on TextRank and convolution neural network

A convolutional neural network and automatic classification technology, applied in the field of educational informatization, can solve problems such as unsatisfactory, and achieve the effect of improving efficiency and reducing interference information

Active Publication Date: 2018-12-21
HUAZHONG NORMAL UNIV
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Problems solved by technology

[0006] At present, most of the research on Chinese text classification is about the binary classification of sentiment classification or the classification of short texts with relatively simple semantics such as news and Weibo. Their general method is to directly use the data set to...

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  • Automatic composition classification method for primary school based on TextRank and convolution neural network
  • Automatic composition classification method for primary school based on TextRank and convolution neural network
  • Automatic composition classification method for primary school based on TextRank and convolution neural network

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[0018] In order to make the object, technical solution and advantages of the present invention clearer, the implementation manner of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0019] Such as figure 1 As shown, the embodiment of the present invention provides a method for automatic classification of primary school composition based on TextRank and character-level convolutional neural network, comprising the following steps:

[0020] (1) Analyze the characteristics of the five types of compositions that are common in primary school compositions: writing about people, narrating, describing scenery, describing things, and feeling after reading, and use this as a standard to correctly divide the data set. The analysis of the characteristics of each type of composition is shown in Table 1.

[0021] Table 1. Characteristics of various types of composition in primary schools

[0022]

[0023] (2) Use the key sen...

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Abstract

The invention belongs to the field of educational informatization, an automatic composition classification method for primary school based on TextRank and convolution neural network is provided, firstly, the TextRank-based key sentence extraction model is used to extract key sentences for various compositions to remove redundant semantic information, and then the convolution neural network is usedto extract fixed-length text feature vectors for training classifiers and predicting text categories. The method of the invention uses TextRank algorithm to eliminate redundant information of data set in advance, and reduces interference information of long text compared with other depth learning methods; the feature selection of the method of the invention is automatically completed, and the efficiency is improved compared with the traditional machine learning method.

Description

technical field [0001] The invention belongs to the field of educational informatization, and relates to an automatic classification method for primary school composition based on TextRank and a convolutional neural network. Background technique [0002] As we all know, reading model essays is an important method for students to learn writing, and reading model essays can significantly improve primary school students' writing performance. Therefore, the rapid construction of model essay material databases is an important link to realize the auxiliary means of writing information. [0003] Text classification is a classic topic in the field of natural language processing. It refers to determining a category for each document in a document collection according to a predefined subject category. With the advent of the data age, the number of electronic documents on the Internet has increased significantly. Text classification has become a key technology in information retrieval ...

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Application Information

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IPC IPC(8): G06F17/30G06N3/04
CPCG06N3/045
Inventor 朱晓亮刘三女牙孙建文石昀东
Owner HUAZHONG NORMAL UNIV
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