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

Stock trend prediction method and system based on text abstract emotion mining

A trend forecasting and stock technology, applied in the field of artificial intelligence, can solve problems such as deviations, and achieve the effect of improving representation ability and accuracy

Inactive Publication Date: 2020-09-29
RENMIN UNIVERSITY OF CHINA
View PDF0 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, when text sentiment analysis techniques are used to automatically extract news sentiment tendencies, there are usually biases

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
  • Stock trend prediction method and system based on text abstract emotion mining
  • Stock trend prediction method and system based on text abstract emotion mining
  • Stock trend prediction method and system based on text abstract emotion mining

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0023] The present embodiment discloses a stock trend prediction method based on sentiment mining of text summaries, comprising the following steps:

[0024] S1 acquires some news data related to stocks.

[0025] Obtaining some news data related to stocks includes: determining the stock target according to the trading volume of the stock, the time interval of the stock listing and the degree of attention, and obtaining the market data of the selected stock; selecting the research object. First of all, it is necessary to consider whether the stock has valid data within the research time range, the number of relevant news, the ranking of stock trading volume, and the ranking of stock returns, so as to ensure that the researched stocks have a high degree of attention. Therefore, when the emotional value of the news changes, It can have an impact on investors' investment psychology and investment decisions. After confirming the selected stock, export the selected stock informatio...

Embodiment 2

[0054] Based on the same inventive concept, this embodiment discloses a stock trend prediction system based on sentiment mining of text abstracts, including:

[0055] The acquisition module is used to acquire some news data related to stocks;

[0056] The abstract generation module is used to obtain the text summary of each news through the news data; the emotion scoring module is used to extract the emotional words in each text abstract according to the pre-established emotional thesaurus, and express the strength of emotion according to the emotional words, Score the sentiment of each text abstract;

[0057] The trend judgment module is used to input the emotional score of each text summary into the pre-established stock prediction model as a feature vector and stock historical trend data for calculation. If the calculation result is greater than or equal to zero, the stock is on an upward trend; if the calculation result is less than Zero, the stock is on a downtrend.

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 stock trend prediction method and system based on text abstract emotion mining. The stock trend prediction method comprises the following steps: S1, acquiring a plurality ofnews data related to stocks; s2, obtaining a text abstract of each piece of news through the news data; s3, extracting sentiment words in each text abstract according to a pre-established sentiment lexicon, and scoring sentiment of each text abstract according to sentiment expression intensity of the sentiment words; s4, inputting the emotion score of each text abstract as a feature vector and stock historical change trend data into a pre-established stock prediction model for calculation, and if a calculation result is greater than or equal to zero, determining that the stock is in an risingtrend; and if the calculation result is less than zero, determining that the stock is in a falling trend. According to the method, news text abstracts are extracted, emotion mining is carried out onthe text abstracts, and information influencing stock market fluctuation trends is effectively obtained, so that stock fluctuation prediction is only limited to previous stock information, and the stock trends can be predicted more accurately from more aspects.

Description

technical field [0001] The invention relates to a stock trend prediction method and system based on sentiment mining of text abstracts, and belongs to the technical field of artificial intelligence. Background technique [0002] China's stock market is an emerging securities market, the market structure and mechanism are not yet mature, and are in the process of continuous exploration and improvement. Compared with mature markets in the West, the investment in my country's stock market is dominated by small and medium-sized investors, whose information acquisition and analysis capabilities and cognitive abilities are unevenly distributed, and the degree of information asymmetry among investors is also higher than that in mature Western capital markets. For a nascent market like China, investors are relatively inexperienced and have many irrational behaviors. Excessive participation of mainstream media will amplify investor sentiment and exacerbate stock market volatility. E...

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): G06F16/2458G06F16/33G06F16/35G06F40/242G06F40/289G06N3/04G06N3/08G06Q40/04
CPCG06F40/289G06F40/242G06F16/2465G06F16/33G06F16/35G06N3/049G06N3/08G06Q40/04G06N3/045
Inventor 齐甜方
Owner RENMIN UNIVERSITY OF CHINA
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