Data association method and device and storage medium

A technology of data association and computing equipment, applied in the direction of network data retrieval, data processing application, network data indexing, etc., to save human resources and avoid the omission of information

Inactive Publication Date: 2018-05-15
上海宽全智能科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In order to overcome the above defects, the present invention proposes a data association method, equipment, and storage medium. By performing multi-dimensional clustering on objects and news information, and then establishing a mapping relationship between objects and news information according to dimensions, the above method is automatically completed by a computer. Avoid the disadvantages of manual screening

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  • Data association method and device and storage medium
  • Data association method and device and storage medium
  • Data association method and device and storage medium

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Experimental program
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Embodiment 1

[0061] This embodiment provides a data association method, which is suitable for execution in the computing device. refer to figure 1 , shows the flow chart of the data association method in this embodiment, including the following steps:

[0062] Step 101, obtain news information, and perform multi-dimensional clustering on the news information by category.

[0063] Wherein, the step 101 can specifically be realized by the following steps, refer to figure 2 , showing a flow chart of the news information clustering method, specifically including:

[0064] Step B1, grabbing original news information and removing duplicate news information.

[0065] Use web crawler technology to crawl original news information, which includes financial news and financial information in blogs and forums. The sources of news information can be Sina Financial News, NetEase Financial News, and financial-related blogs and forums to remove duplication news information.

[0066] Step B2, extract ...

Embodiment 2

[0094] Embodiment 2 of the present invention is regarded as a further improvement process of the data association method described in Embodiment 1. Refer to figure 2 , shows a flow chart of the data association method in Embodiment 2 of the present invention. Steps 201 to 203 are the same as Steps 101 to 103 in Embodiment 1, and will not be repeated here. The difference from Embodiment 1 is that this embodiment also includes:

[0095]Step 204, calculating the emotional index of the news information and the associated object, the calculation method of the emotional index includes:

[0096] (A1) Calculate the similarity between each piece of news information and each associated object according to the mapping relationship;

[0097] (A2) Calculate the emotional index of the object according to the similarity, the calculation method of the emotional index is as follows:

[0098] Mood index M=K*S*W,

[0099] Wherein, K is an emotion coefficient, which is preset as 1 in this emb...

Embodiment 3

[0111] The third embodiment of the present invention is regarded as another improvement process of the data association method described in the second embodiment, refer to image 3 , shows a flow chart of the data association method in Embodiment 3 of the present invention. Steps 301 to 304 are the same as Steps 101 to 104 in Embodiment 1, and will not be repeated here. The difference from Embodiment 2 is that this embodiment also includes:

[0112] Step 305, establish the correlation between the clustered objects according to the dimension, and sort according to the magnitude of the correlation.

[0113] In this embodiment, the correlation among clustering objects is established according to the sector dimension, the region dimension, the industry dimension, the personnel dimension and the enterprise scale dimension respectively. The correlation can be determined by the similarity between the clustering objects. Specifically, the similarity between the standard words defined...

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Abstract

The invention provides a data association method and device and a storage medium, and relates to the field of finance. The method comprises the steps of obtaining news information, and the news information is subjected to multi-dimensional clustering according to categories; obtaining information messages of multiple objects, and on the basis of the information messages, performing multi-dimensional clustering on the objects; according to the dimensions, building the mapping relation between the clustered objects and the clustered news information; displaying a result. By building the mappingrelation between the objects and the news information according to the dimensions, associated information can be automatically triggered, the information associated with the data association method iscomprehensive, information omission is avoided, more comprehensive information can be provided for an investor for reference, and more reasonable decisions are made; by building correlation among theclustered objects, ranking is performed according to the correlation among the clustered objects, a warning can be given to the investor in advance by building the correlation among the clustered objects, and decisions are made in advance.

Description

technical field [0001] The present invention relates to the financial field, in particular, to a data association method, device and storage medium in the field of financial data processing. Background technique [0002] The securities market and financial investment occupy an important position in modern society. The modeling and forecasting research of the stock market is of great significance to my country's economic development and financial construction, and has always been concerned by people. The stock market is affected by many factors such as national policies, economic situation, company development status and investor psychology. [0003] Common stock market forecasting methods include securities investment analysis methods, time series forecasting analysis methods, and nonlinear forecasting methods. Securities investment analysis method includes fundamental analysis method and technical analysis method. Fundamental analysis mainly includes macroeconomic analysi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06Q40/06
CPCG06F16/35G06F16/951G06Q40/06
Inventor 陈盛福李贵
Owner 上海宽全智能科技有限公司
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