Calculation method and system for relevance degree of individual share and article

A calculation method and correlation technology, which is applied in the correlation analysis method and system field between individual stock entities and articles, and can solve problems such as high noise, no description of the correlation between individual stocks and articles, and no time dimension

Inactive Publication Date: 2016-07-06
NAT UNIV OF DEFENSE TECH
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AI Technical Summary

Problems solved by technology

[0003] 1. Loud noise: There are many promotional links in advertisements. Generally, the search results of advertisements are ranked at the top; semantic errors, search engines mainly obtain search results based on keywords, not at the semantic level. When there is ambiguity, there are many inaccurate results
[0004] 2. High degree: For hot news information, all major websites will report; in many cases, the title and content are exactly the same, but search engines will not help you remove duplication
[0005] 3. Lack of key indicators: The results of search en...

Method used

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  • Calculation method and system for relevance degree of individual share and article
  • Calculation method and system for relevance degree of individual share and article
  • Calculation method and system for relevance degree of individual share and article

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Embodiment Construction

[0071] Below in conjunction with accompanying drawing, the present invention will be further described:

[0072] refer to figure 1 , a system for calculating the degree of association between individual stocks and articles, the system includes a data acquisition module, an association degree analysis module, a sentiment analysis module, a heat analysis module, a data storage module and a data retrieval module, and the data acquisition module crawls from the Internet in real time Get and obtain finance and economics class news as corpus and file storage; Described correlation degree analysis module is connected with data acquisition module, and correlation degree analysis module analyzes the association relation of individual stock and article in the corpus that obtains in real time, calculates degree of association; Described sentiment analysis The module is connected with the data acquisition module, and the emotional analysis module analyzes the individual stock emotion in t...

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Abstract

The present invention discloses a calculation method and system for relevance degree of an individual share and an article. The system comprises a data acquisition module, a relevance degree analysis module, an emotion analysis module, a heat analysis module, a data storage module and a data retrieval module. The method comprises: acquiring massive financial news corpus every day; performing text data mining; analyzing a relevance between an individual share and an article among the corpus that is acquired in real time; analyzing individual share emotion in the corpus that is acquired in real time; summarizing the relevance between the individual share and the article, i.e. heat of the individual share daily; enabling an investor to retrieve market condition news of a share that draws the attention of the investor, and providing the relevance degree with the article, and historical heat indicators of the emotion and share for reference, so that the method and system become an excellent retrieval tool of the investor for individual share market condition news.

Description

technical field [0001] The invention relates to the correlation analysis between entities and massive articles, in particular to a correlation analysis method and system for individual stock entities and articles. Background technique [0002] At present, information related to individual stocks is mainly retrieved through search engine tools. This method has the following disadvantages: [0003] 1. Loud noise: There are many promotional links in advertisements. Generally, the search results of advertisements are ranked at the top; semantic errors, search engines mainly obtain search results based on keywords, not at the semantic level. When there is ambiguity, there are many inaccurate results. [0004] 2. High degree: For hot news information, all major websites will report; in many cases, the title and content are exactly the same, but search engines will not help you remove duplication. [0005] 3. Lack of key indicators: The results of search engines generally only sh...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06F17/27
CPCG06F16/35G06F40/216G06F40/289
Inventor 陈发君黄金才刘忠程光权朱承修保新陈超冯旸赫
Owner NAT UNIV OF DEFENSE TECH
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