Identification method of emotional tendency of network comment texts and convolutional neutral network model

A technology for network comments and emotional tendencies, applied in the field of recognition methods for emotional tendencies and convolutional neural network models, can solve problems such as misclassification of adversarial samples, and achieve the effects of improving robustness, improving effects, and improving quality

Active Publication Date: 2017-08-08
CENT SOUTH UNIV
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Problems solved by technology

[0007] The purpose of the present invention is to provide an identification method and a convolutional neural network model for the emotional tendency of network comment texts, so as to solve the technical problem of misclassifying adversarial samples in the existing methods

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  • Identification method of emotional tendency of network comment texts and convolutional neutral network model
  • Identification method of emotional tendency of network comment texts and convolutional neutral network model
  • Identification method of emotional tendency of network comment texts and convolutional neutral network model

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Embodiment Construction

[0041] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings, but the present invention can be implemented in many different ways defined and covered by the claims.

[0042] The following are some definitions of terms used in this embodiment:

[0043] word vector:

[0044] In the field of natural language processing, the traditional vocabulary representation uses one-hot representation, which represents each word as a high-dimensional sparse vector, and the dimension of the vector is the size of the entire vocabulary, except for the representation of the vocabulary The elements of are 1, and the rest are 0. For example, the words "computer" and "computer" are represented as follows:

[0045] computer: [0,0,0,1,0,0,…]

[0046] computer: [0,1,0,0,0,0,…]

[0047] The disadvantage of this method is that it not only wastes a lot of storage space, but also has the phenomenon of "lexical gap". Even if words such as ...

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Abstract

The invention discloses an identification method of emotional tendency of network comment texts and a convolutional neutral network model. The method comprises the steps as follows: grabbed network comment texts constitute a data set; word segmentation and text preprocessing are performed; all words subjected to text preprocessing are trained, and word vector representation of all words is obtained; the convolutional neutral network model is constructed and trained on a training set selected from the data set, and network parameters are updated with a back-propagating algorithm; in each step of training, noise is added to word vectors of an input layer for construction of adversarial samples, adversarial training is performed, and network parameters are updated with a random gradient descent algorithm; a classification model is obtained through repeated iteration to identify the emotional tendency of the network review texts. The convolutional neutral network model is used in the method and comprises the input layer, a convolution layer, a pooling layer and a classification layer. The adversarial samples can be classified correctly and the identification accuracy is improved.

Description

technical field [0001] The invention relates to the technical field of natural language processing, in particular to a recognition method and a convolutional neural network model of an emotional tendency of a network comment text. Background technique [0002] With the rapid development of the Internet, network users have released rich text information on various network platforms, such as service evaluations and product reviews. Mining the emotional features of network users' commentary texts and identifying the emotional tendencies of these texts has important application significance in market analysis, public opinion analysis, and information prediction. Text sentiment orientation recognition, also known as text sentiment analysis, refers to the process of analyzing, processing, inducing and inferring subjective texts with emotional characteristics. Its main purpose is to divide comment texts into "positive" and "negative". kind. At present, there are mainly three type...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06F17/27G06K9/62G06N3/08
CPCG06F16/353G06N3/08G06F40/232G06F40/284G06F18/2411
Inventor 郑瑾田星张祖平宋冬云李俊
Owner CENT SOUTH UNIV
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