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

Text emotion classifying method in stock field

A sentiment classification, stock technology, applied in special data processing applications, instruments, electrical digital data processing and other directions, can solve problems such as high prices

Inactive Publication Date: 2011-04-20
TSINGHUA UNIV
View PDF0 Cites 52 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the services provided by these companies are generally at a high price, which is beyond the reach of ordinary investors

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
  • Text emotion classifying method in stock field
  • Text emotion classifying method in stock field
  • Text emotion classifying method in stock field

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0058] The present invention proposes a text sentiment classification method facing the stock field, and the method is carried out in the computer according to the following three steps successively, and the specific process is as follows: figure 1 Shown:

[0059] Step (1) text preprocessing.

[0060] Text preprocessing is mainly divided into two processes: Chinese text word segmentation and stop word removal, among which:

[0061] 1. Chinese text word segmentation:

[0062] Chinese text word segmentation refers to the segmentation of Chinese character sequences into words with independent meaning, which is the basis for Chinese natural language processing. It needs to be done in two steps:

[0063] The first step is to build a word segmentation dictionary in the stock field based on the n-gram statistical language model:

[0064] In the field of Chinese word segmentation, there are two concepts of new words (New Words) and unregistered words (UnknownWords), but sometimes ...

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 text emotion classifying method in the stock field, belonging to the technical field of stock tendentiousness analysis. The text emotion classifying method is characterized in that feature selection is carried out on an enlarged stock emotion word through public news information comprising stock news and the like and by using an improved evaluation group; feature weighting selection is carried out on emotion word in the stock Chinese text by using absolute word frequency weighting; and finally, tendentiousness analysis is carried out on stock news by using a Bayes, K-NN or SVM (support vector machine) text emotion classifying algorithm. The method provided by the invention has the advantages of simplicity and feasibility, and is convenient for calculation.

Description

technical field [0001] The invention belongs to the field of text sentiment classification of natural language processing, and in particular relates to a text sentiment classification method facing the stock field. Background technique [0002] With the development of the economy and the improvement of people's living standards, it has gradually become the general trend of today's society to invest and manage money by buying stocks. How to buy stocks accurately has become a matter of great concern to investors. At the same time, with the rapid development of network technology, the network has gradually replaced traditional news media as the main way for people to obtain information due to its real-time, richness, and coverage. More and more stock news appears on the Internet. These news include macroeconomic news, stock-related news, industry news, listed company news and so on. [0003] Efficient Market Theory (EMH: Efficient Markets Hypothesis), also known as the Efficie...

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): G06F17/27G06F17/30
Inventor 张勇高旸周莉邢春晓
Owner TSINGHUA 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