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

Microblog emotion prediction method based on multi-mode hypergraph learning

A prediction method and multi-modal technology, applied in other database retrieval, network data retrieval, instruments, etc., can solve problems such as less content, difficult emotion category analysis, and low accuracy of emotion prediction

Inactive Publication Date: 2017-05-31
XIAMEN UNIV
View PDF9 Cites 23 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The existing technology is mainly aimed at the sentiment analysis of microblogs with a single text channel, and the text of microblogs has the characteristics of random structure and less content. The prediction accuracy is low

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
  • Microblog emotion prediction method based on multi-mode hypergraph learning
  • Microblog emotion prediction method based on multi-mode hypergraph learning
  • Microblog emotion prediction method based on multi-mode hypergraph learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0062] Embodiments of the present invention include the following steps:

[0063] Step 1 extracts microblog multimodal features (Feature Extraction), the specific method is as follows:

[0064] Step 1.1 For the text mode, first use the automatic word segmentation tool ICTCLAS of the Chinese Academy of Sciences to segment the microblog text content (Text segment), and then use the processed Chinese sentiment dictionary (Text word dictionary) to construct words for each microblog text after word segmentation Bag-of-textual-word, as the text sentiment feature after the final screening, the Chinese sentiment dictionary is composed of HowNet Chinese sentiment dictionary and National Taiwan University NTUSD Chinese sentiment dictionary, and screened out text corpus in Weibo The 2547 emotional words with higher frequency appearing in the Chinese emotional dictionary are composed of them. The i-th microblog text feature is denoted as F i botw ;

[0065] Step 1.2 For the visual mod...

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 microblog emotion prediction method based on multi-mode hypergraph learning and belongs to the field of multi-mode emotion analysis. The microblog emotion prediction method based on multi-mode hypergraph learning is provided aiming at the problems existing in emotion prediction on microblog multi-channel content. The method includes the following steps that 1, microblog multi-mode features are extracted; 2, the distance between microblog is calculated; 3, a multi-mode hypergraph model is established; 4, hypergraph learning is carried out. Different modes can be better associated to solve the problem of independence between the modes, and a good effect is achieved on microblog emotion prediction.

Description

technical field [0001] The invention belongs to the field of multimodal emotion analysis, and in particular relates to a microblog emotion prediction method based on multimodal hypergraph learning. Background technique [0002] Recently, with the rapid development of large social platforms such as Sina Weibo, the scale of multimedia data in social networks is increasing every day. Taking Sina Weibo as an example, as of May 2014, the monthly active users of Sina Weibo reached 140 million. It was up 10.9% in December 2013. As one of the most popular platforms, Sina Weibo enables Internet users to express their emotions on topics of interest to them. Therefore, it has attracted a large amount of research on emotional information mining, which involves some emerging applications including event detection, social network analysis, and business recommendation. [0003] An obvious feature of the development of Weibo is the growth of multimodal information, such as images, videos,...

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): G06F17/27G06F17/30G06Q50/00
CPCG06F16/951G06F40/289G06Q50/01
Inventor 纪荣嵘曹冬林陈福海
Owner XIAMEN UNIV
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