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Enterprise risk early warning method and system based on knowledge graph

A knowledge graph and risk early warning technology, applied in the field of enterprise risk early warning methods and systems based on knowledge graphs, can solve problems such as difficulty in adapting, reducing the accuracy of enterprise risk early warning results, single data source structure, etc., and achieve the goal of improving accuracy Effect

Pending Publication Date: 2020-11-06
南京星云数字技术有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the rapid increase in the amount of data, the requirements for data analysis and understanding have far exceeded human physiological limits, which poses new requirements and challenges for the analysis method
The traditional data processing and text search methods have been difficult to adapt to the rapidly changing market conditions, and cannot meet the real-time, penetrating and overall requirements of financial analysis
[0003] The data source structure obtained by existing financial analysis is single, and risk factors can only be mined from structured data, and relevant unstructured data cannot be used, such as public web page text information, and these public web page text information often contains effective risk factors
In summary, due to the single structure of data sources, the accuracy of enterprise risk warning results is reduced.

Method used

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  • Enterprise risk early warning method and system based on knowledge graph
  • Enterprise risk early warning method and system based on knowledge graph
  • Enterprise risk early warning method and system based on knowledge graph

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0046] see figure 1 , this embodiment provides a knowledge map-based enterprise risk early warning method, including:

[0047] Obtain structured and semi-structured data about enterprise information, form standardized structured data after processing and import it into the data pool; obtain unstructured data about enterprise information, form enterprise relationship data after processing and import it into the corpus; based on the data in the data pool Standardized structural data and enterprise relationship data in the corpus construct the knowledge map of the target enterprise; use the pre-trained risk identification model to mine the risk information of the target enterprise from the knowledge map to realize risk warning.

[0048] The enterprise risk early warning method based on the knowledge graph provided in this embodiment first obtains structured data and semi-structured data about enterprise information, forms standardized structured data after processing and imports ...

Embodiment 2

[0078] This embodiment provides a knowledge map-based enterprise risk early warning system, including:

[0079] The data pool unit is used to obtain structured data and semi-structured data about enterprise information, and after processing, it forms standardized structured data and imports it into the data pool;

[0080] The corpus unit is used to obtain unstructured data about enterprise information, and after processing, it forms enterprise relational data and imports it into the corpus;

[0081] A knowledge map construction unit, based on the standardized structure data in the data pool and the enterprise relationship data in the corpus, constructs the knowledge map of the target enterprise;

[0082] The risk early warning unit uses the pre-trained risk identification model to mine the risk information of the target enterprise from the knowledge map to realize risk early warning.

[0083] Preferably, the data pool unit includes:

[0084] A template configuration module, ...

Embodiment 3

[0089] This embodiment provides a computer-readable storage medium. A computer program is stored on the computer-readable storage medium. When the computer program is run by a processor, the steps of the above-mentioned enterprise risk warning method based on knowledge graph are executed.

[0090] Compared with the prior art, the beneficial effect of the computer-readable storage medium provided by this embodiment is the same as the beneficial effect of the enterprise-related risk early warning method provided by the above technical solution, and will not be repeated here.

[0091]Those of ordinary skill in the art can understand that all or part of the steps in the above inventive method can be completed by instructing related hardware through a program. The above program can be stored in a computer-readable storage medium. When the program is executed, it includes: For each step of the method in the above embodiments, the storage medium may be: ROM / RAM, magnetic disk, optical...

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Abstract

The invention discloses an enterprise risk early warning method and system based on a knowledge graph, and relates to the technical field of artificial intelligence. The method comprises the followingsteps: acquiring structured data and semi-structured data of enterprise information, processing to form standardized structured data, and importing the standardized structured data into a data pool;acquiring unstructured data of the enterprise information, processing the unstructured data to form enterprise relationship data, and importing the enterprise relationship data into a corpus; constructing a knowledge graph of a target enterprise based on the standardized structure data in the data pool and the enterprise relationship data in the corpus; and mining the risk information of the target enterprise from the knowledge graph by using a pre-trained risk identification model to realize risk early warning. The system applies the method mentioned above.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to a method and system for early warning of enterprise risks based on knowledge graphs. Background technique [0002] Financial big data analysis and semantic processing of text in the financial field are key basic technologies for knowledge extraction in the financial industry, which can provide technical support for knowledge discovery and reasoning decision-making. Therefore, more and more financial institutions and enterprises have joined in the construction of enterprise risk early warning research in the financial field to provide accurate and reliable basis for enterprise application decision-making. Due to its strong dependence on data, the financial field is considered to be one of the most suitable fields for artificial intelligence technology. Massive data provide people with more and more abundant sources to better grasp and recognize the laws of ...

Claims

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Application Information

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IPC IPC(8): G06Q40/02G06F16/36G06F40/295G06K9/62
CPCG06F16/367G06F40/295G06Q40/03G06F18/24323
Inventor 沈春泽李加庆周张泉孙华蔚
Owner 南京星云数字技术有限公司
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