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)
View PDF11 Cites 40 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, these methods are not very good at iden

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • 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

Examples

Experimental program
Comparison scheme
Effect test

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 [...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

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

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
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)
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap