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Neural network based analyzing method for recognizing emotional tendency of text comments

A technology of neural network recognition and emotional tendency, which is applied in the field of computer language and word processing, and can solve problems such as the inability to recognize the emotional tendency of text comments

Inactive Publication Date: 2017-09-12
NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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  • Description
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  • Application Information

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Problems solved by technology

Therefore, these methods are not very good at identifying the sentiment orientation of text comments

Method used

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  • Neural network based analyzing method for recognizing emotional tendency of text comments
  • Neural network based analyzing method for recognizing emotional tendency of text comments
  • Neural network based analyzing method for recognizing emotional tendency of text comments

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Embodiment Construction

[0066] The present invention proposes an analysis method for identifying the emotional tendency of text comments based on a neural network, which will be described below in conjunction with the accompanying drawings.

[0067] The present invention uses a continuous bag-of-words CBOW model (Continuous Bag-of-Words Model) for processing text comment data. As a method of training word vectors, and then use the long short-term memory LSTM model (Long Short TimeMemory, LSTM) to judge the emotional tendency of comments; figure 1 The specific steps shown in the flowchart are as follows:

[0068] The first step is corpus preprocessing, which accurately divides each sentence into words or words; each sentence has a corresponding category label, that is, 0, 1, and 2, which represent negative, neutral, and positive respectively; here we need Convert each category label into a three-dimensional vector, that is, 0 is converted to [1 0 0], 1 is converted to [0 1 0], and 2 is converted to [...

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Abstract

The invention discloses a neural network based analyzing method for recognizing emotional tendency of text comments, and belongs to the technical field of computer language and work processing. The method is characterized in that the text comment data are processed through CBOW; each sentence is accurately divided into words or terms, and each sentence is provided with a corresponding class label; the emotional tendency of the comments is determined through a long-and-short term memory LSTM model; the label of each sentence is obtained and compared with a true label to obtain the accuracy rate; and a neural network model is trained to obtain the optimal accuracy rate, thus achieving the purpose of recognizing the emotional tendency of the text comments based on the neural network. According to the method, the GPU is utilized to accelerate the neural network training process, so that the emotion classing accuracy rate is increased, and moreover, the mass corpus data training speed is increased; the emotional tendency of the comments can be effectively recognized; and the method particularly has a good application prospect on e-commerce, film and other fields.

Description

technical field [0001] The invention belongs to the technical field of computer language and word processing, and in particular relates to an analysis method for identifying the emotional tendency of text comments based on a neural network. Background technique [0002] With the continuous development and popularization of the computer Internet, people urgently need to manage the increasingly rich text comment resources on the Internet, and realize the effective and accurate sentiment classification of massive text comment resources. Traditional text sentiment classification is considered as a text classification task, which is far from being able to accurately judge the sentiment orientation of text comments. [0003] Sentiment analysis is to accurately classify the emotions expressed in text comments, helping people to identify the emotional tendency of comments conveniently and quickly. At present, the method of text comment sentiment classification can refer to the lite...

Claims

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Application Information

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IPC IPC(8): G06F17/27G06N3/08
CPCG06F40/211G06F40/284G06F40/289G06F40/30G06N3/08
Inventor 何慧冷永才胡然张莹焦润海
Owner NORTH CHINA ELECTRIC POWER UNIV (BAODING)
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