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

Chinese microblog viewpoint sentence recognition feature extraction method based on self-adaption lifting algorithm

A technology for identifying features and extracting methods, applied in computing, special data processing applications, natural language data processing, etc., can solve problems such as lack of classification methods and feature combination optimization methods, and analysis difficulties in syntactic structures

Inactive Publication Date: 2014-06-25
HUAQIAO UNIVERSITY
View PDF8 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the limitation of the number of words, the frequency of words, parts of speech, and dependencies is greatly reduced compared with ordinary text; because of the freedom of language structure, it is relatively difficult to analyze the syntactic structure
For the subjective component feature recognition of short texts such as Chinese microblogs, there is still a lack of systematic and effective classification methods and combined optimization methods for feature extraction.

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
  • Chinese microblog viewpoint sentence recognition feature extraction method based on self-adaption lifting algorithm
  • Chinese microblog viewpoint sentence recognition feature extraction method based on self-adaption lifting algorithm
  • Chinese microblog viewpoint sentence recognition feature extraction method based on self-adaption lifting algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0032] Please check figure 1 To identify Chinese microblog opinion sentences, we must first set the features related to the recognition of microblog opinion sentences, and then extract the most effective recognition from many related features according to the Chinese microblog opinion sentence recognition feature extraction method based on the adaptive lifting algorithm. feature.

[0033] In the present embodiment, adopt the part of speech in Chinese micro-blog and the emotional word set in the sentiment dictionary as the basic identification feature, part of speech includes adjective, verb, interjection, etc., adopt the ICTPOS Chinese part of speech tag set of Institute of Computing Technology, Chinese Academy of Sciences except for punctuation marks In the process of extracting the identification features of opinion sentences, we have established a weak classifier for each part of speech, that is, each part of speech classifier is used to match a part of speech. The emotion...

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 Chinese microblog viewpoint sentence recognition feature extraction method based on a self-adaption lifting algorithm. The method comprises the steps that firstly, features related to recognizing a microblog viewpoint sentence are set and recognized, weak classifiers with single features form a strong classifier with a plurality of features, and critical recognition features are selected in the construction process of the strong classifier; finally, an effective subjective sentence recognition feature set and the strong classifier formed by the recognition feature set are output, and effective recognition bases can be provided for recognition of the Chinese microblog viewpoint sentence through the subjective sentence recognition feature set.

Description

technical field [0001] The invention relates to a method for extracting recognition features of Chinese microblog opinion sentences based on an adaptive lifting algorithm. Background technique [0002] It is an important basis for automatic collection and analysis of network Chinese public opinion data to effectively determine whether people's views, opinions or tendencies on things are included in Chinese microblogs. From the perspective of text mining, identifying subjective sentences can improve the accuracy of opinion classification and reduce the interference of non-subjective sentences on subsequent natural language processing related tasks such as opinion summary, tendency statistics and sentiment analysis. [0003] With the rapid development of the Internet and the popularization of Web2.0, the publication of information is no longer the exclusive property of newspapers, magazines, TV stations and news websites, and microblog websites have become the media for releas...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06F17/27
CPCG06F16/35G06F40/211
Inventor 陈锻生吴扬扬方圆
Owner HUAQIAO UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com