Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Classification method based on neural network and classification device thereof

A neural network and classification method technology, applied in neural learning methods, biological neural network models, instruments, etc., can solve the problem of low classification performance and achieve the effect of high classification performance

Inactive Publication Date: 2017-01-18
SUZHOU UNIV
View PDF4 Cites 9 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In view of this, the object of the present invention is to provide a classification method and device based on neural network, aiming to solve the problem of low classification performance in the current linear classification method, so as to further improve the classification performance of emotion classification

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
  • Classification method based on neural network and classification device thereof
  • Classification method based on neural network and classification device thereof
  • Classification method based on neural network and classification device thereof

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0051] Embodiment 1 of the present invention provides a neural network-based classification method, which is suitable for but not limited to sentimental polarity classification of text data, refer to figure 1 The flow chart of the classification method shown, the method may include the following steps:

[0052] S101: Obtain training samples.

[0053] This embodiment uses emotion classification as an example to illustrate the method of the present application. Specifically, this embodiment proposes an emotion classification scheme based on a neural network.

[0054]Among them, Artificial Neural Networks (ANN): It appeared after the 1940s. It is connected by a large number of neurons with adjustable connection weights, and has the characteristics of large-scale parallel processing, distributed information storage, and good self-organizing and self-learning capabilities. The BP (Back Propagation) algorithm, also known as the error backpropagation algorithm, is a supervised lear...

Embodiment 2

[0104] In the second embodiment, refer to image 3 The shown flow chart of the classification method based on the neural network, the method may also include the following steps:

[0105] S104: Verify the classification accuracy of the classifier based on the classification category and the actual category of the sample to be tested.

[0106] This embodiment specifically verifies the accuracy of the classifier trained based on the convolutional neural network classification method in Embodiment 1. In the examples of the four subject data provided in this application, specifically 4000 items of each subject after 2012 The comment text is used as the sample to be tested, and the classifier trained based on the convolutional neural network classification method is used to classify the sample to be tested.

[0107] On the basis of the classification, the category label obtained by classification is compared with the actual category of the 4000 comment texts in each topic (if the ...

Embodiment 3

[0113] Embodiment 3 discloses a neural network-based classification device, which corresponds to the neural network-based classification methods disclosed in the above embodiments.

[0114] Corresponding to embodiment one, refer to Figure 4 A schematic structural diagram of a classification device based on a neural network is shown, which may include a sample acquisition module 100 , a sample processing module 200 and a classifier construction module 300 .

[0115] The sample acquisition module 100 is configured to acquire training samples.

[0116] The sample acquisition module 100 includes a text capture unit, configured to capture a predetermined number of text data from a predetermined data source, and use the captured text data as a training sample.

[0117] The sample processing module 200 is configured to perform distributed semantic representation processing on the training samples to obtain the distributed semantic representation of the training samples.

[0118] T...

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 classification method based on a neural network and a classification device thereof. According to the method and the device, distributed semantic representation processing is performed on training samples so that distributed semantic representation of the training samples is obtained; and the sample characteristics of the training samples of the distributed semantic representation form are learned based on a convolutional neural network classification mode so that finally a classifier is constructed according to the learning result of the sample characteristics, and the classifier can be utilized to classify the samples to be tested subsequently. Therefore, the classification scheme based on the neural network is realized, and the sample characteristics of the training samples can be more effectively learned by the classification method based on the neural network in comparison with the conventional linear classification method of maximum entropy classification and support vector machine classification so that higher classification performance can be brought.

Description

technical field [0001] The invention belongs to the field of natural language processing and pattern recognition, in particular to a neural network-based classification method and device. Background technique [0002] With the rapid development of the Internet, online transactions are becoming more and more popular, followed by more and more commodity reviews on the Internet, forming a large amount of review text information. These massive text information generally have obvious emotional color and are of high value. Sentiment analysis and research on them can provide effective help to enterprises, governments, and individuals in making decisions. [0003] Since sentiment analysis was proposed by Bo Pang in 2002, it has obtained a large degree of research, especially in the sentiment analysis of online comments. Sentiment classification is an important research task in sentiment analysis. It mainly realizes the classification of texts according to the opinions and attitudes...

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): G06K9/62G06N3/08
CPCG06N3/08G06F18/24133G06F18/214
Inventor 李寿山张栋周国栋
Owner SUZHOU UNIV
Features
  • Generate Ideas
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

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

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com