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

Multi-feature fusion Chinese-over-the-sea news viewpoint sentence extraction method

A multi-feature fusion, opinion sentence technology, applied in special data processing applications, biological neural network models, unstructured text data retrieval, etc.

Active Publication Date: 2019-11-19
KUNMING UNIV OF SCI & TECH
View PDF10 Cites 15 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a Chinese-Vietnamese news opinion sentence extraction method with multi-feature fusion, which solves the problem of Chinese-Vietnamese news opinion sentence extraction, and can effectively improve the Chinese-Vietnamese news opinion sentence extraction method. The Accuracy of News Opinion Sentence 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
  • Multi-feature fusion Chinese-over-the-sea news viewpoint sentence extraction method
  • Multi-feature fusion Chinese-over-the-sea news viewpoint sentence extraction method
  • Multi-feature fusion Chinese-over-the-sea news viewpoint sentence extraction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0060] Embodiment 1: as Figure 1-3 As shown, a Chinese-Vietnamese news opinion sentence extraction method with multi-feature fusion includes the following specific steps:

[0061] (1) Select 35,000 Chinese and Vietnamese news articles and 10W Chinese-Vietnamese parallel sentence pairs from the Chinese-Vietnamese news corpus to train Chinese-Vietnamese bilingual word vectors. 1367 opinion sentences of Vietnamese news and 8552 opinion sentences of Chinese news were manually selected and marked as the data set of Chinese-Vietnamese news opinion sentences extraction. The training set, test set, and verification set accounted for 90%, 5%, and 5% of the data set, respectively. Among the Chinese-Vietnamese bilingual sentiment dictionaries used, the scale of the Chinese sentiment dictionary is 4626, and the scale of the Vietnamese sentiment dictionary is 2939;

[0062] (2) Use 35,000 Chinese-Vietnamese news texts and 10W Chinese-Vietnamese parallel sentence pairs to train the Chine...

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 relates to a multi-feature fusion Chinese-overtopped news viewpoint sentence extraction method, and belongs to the technical field of natural language processing. Firstly, a cross-language representation learning method is adopted to construct a Chinese-Vietnamese bilingual word embedding model; and then calculating feature weights of the topic, emotion and position of the sentence,and fusing the feature weight information into a coding layer and an attention mechanism to obtain representation of the sentence in the aspects of topic, emotion, position and the like. And finally,viewpoint sentence classification is carried out according to the obtained sentence representation. Aiming at the problem that Chinese and Vietnamese marking resources are unbalanced, a Chinese-Vietnamese bilingual word embedding model is constructed; according to the method, the sentences are extracted from the sentences, then the weights of the topics, the positions and the sentiment features ofthe sentences are calculated respectively, the sentence weights are fused into the word vectors and the attention mechanism respectively, sentence semantic information and the sentiment, topic and position features are combined, and the accuracy of extracting the sentences of the Hami news viewpoints can be effectively improved.

Description

technical field [0001] The invention relates to a Chinese-Vietnamese news opinion sentence extraction method with multi-feature fusion, and belongs to the technical field of natural language processing. Background technique [0002] How to quickly and accurately automatically search and obtain news opinion sentences in massive Internet news information pages has gradually become a strong demand of people and has a very important application prospect. In the opinion sentence extraction task, the existing methods mainly extract the opinion sentences in the document based on the characteristics of the opinion sentences. For example, the hidden Markov model is used to sequentially mark sentences, and different weights are given to sentences to realize the recognition of opinion sentences. Or obtain the word set of opinion words and non-view words through a dictionary, then calculate the strength of the opinion words, and finally judge the opinion sentence by the strength of the...

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): G06F16/35G06N3/04
CPCG06F16/35G06N3/049
Inventor 余正涛唐珊王剑相艳林思琦郭军军线岩团
Owner KUNMING UNIV OF SCI & TECH
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