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

Semantic analysis technology-based sensitive public sentiment content recognition method and pre-warning system

A technology of semantic analysis and content recognition, applied in the fields of information security, education, and information technology, can solve problems such as low efficiency, and achieve the effect of improving accuracy and accuracy rate

Active Publication Date: 2018-04-17
广州思涵信息科技有限公司 +1
View PDF10 Cites 13 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the field of classroom teaching of ideological and political courses, at present, it mainly relies on manual lectures (on-site lectures or video review) for teaching review, which is very inefficient

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
  • Semantic analysis technology-based sensitive public sentiment content recognition method and pre-warning system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0052] Such as figure 1 As shown, a sensitive public opinion content identification method based on semantic analysis technology includes the following steps:

[0053] S1: Establish the vector lexicon of sensitive words: import the vector lexicon of sensitive words, classify the sensitive words, set a core word as the reference word for each type of sensitive words, and use it as the source node to set the distance from other similar words to the reference word vector;

[0054] In step S1, establishing a sensitive thesaurus includes the following steps:

[0055] S1.1: Import commonly used Chinese word segmentation benchmark thesaurus;

[0056] S1.2: Establish a special sensitive word vector library;

[0057] S1.3: Classify sensitive words, set a core word as a reference word for each type of sensitive words, and use it as a source node to set distance vectors from other similar words to the reference word.

[0058]For example: in words such as political parties, with "posi...

Embodiment 2

[0085] An early warning system for sensitive public opinion content based on semantic analysis technology, including:

[0086] Sensitive thesaurus: used to import sensitive word vector thesaurus, classify sensitive words, set a core word as the reference word for each type of sensitive word, and use it as the source node to set the distance vector from other similar words to the reference word;

[0087] Speech recognition processing module: used for speech recognition of audio files, identifying sensitive words and related emotional words;

[0088] Sensitive content positioning module: used for cluster analysis, identifying sensitive words and emotional words related to semantics, and performing semantic correction;

[0089] Output module of analysis results: used to identify and output sensitive content.

[0090] This embodiment provides an early warning system for sensitive public opinion content based on semantic analysis technology, which realizes identification, accurate...

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 provides a semantic analysis technology-based sensitive public sentiment content recognition method and a pre-warning system. The method comprises the following steps of: importing a Chinese word segmentation standard lexicon, increasing a sensitive word vector library, classifying sensitive words, setting a core word as a standard word for each type of sensitive words, and setting distance vectors from other same-type words to the standard word by taking the standard word as a source node; carrying out voice recognition on an audio file, and recognizing sensitive words and related sentiment words; carrying out clustering analysis, recognizing sensitive words and sentiment words related to semantic meaning, and carrying out semantic analysis judgement; and recognizing and outputting sensitive contents. According to the method, the sensitive word vector library is established on the basis of a traditional natural language lexicon, and vector distance relationship among same-type sensitive words is established. In practical application field, sensitive content recognition and pre-warning can be automatically carried out on real-time communication contents or classroom teaching contents. By utilizing the method, sensitive sematic judgement can be realized and the correctness is greatly enhanced so that sensitive public sentiment content monitoring is realized.

Description

technical field [0001] The present invention relates to the fields of information technology, information security and education technology, and more specifically, to a method for identifying sensitive public opinion content based on semantic analysis technology and an early warning system. Background technique [0002] Speech recognition technology and natural language processing are widely used in various fields such as communications, industry, home appliances, Internet of Vehicles, medical care, home services, and consumer electronics. [0003] In the field of information security, especially in the identification of sensitive content in the communication process, the current main approach is to rely on sensitive word labeling and word frequency statistics, and there is no analysis of semantics, so there is a relatively large false positive rate. [0004] In the field of educational technology, the application of speech recognition technology is limited to spoken languag...

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): G06F17/30G06F17/27
CPCG06F16/3344G06F40/284G06F40/30
Inventor 李昊林南晖郑凯黄叶敏
Owner 广州思涵信息科技有限公司
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