Public opinion information extraction and knowledge base generation method based on natural language processing

A natural language processing and information extraction technology, applied in special data processing applications, semantic tool creation, text database query, etc., can solve the problem of limited investigation depth and query efficiency, and it is difficult to meet the dynamic query needs of financial institution group customer related information, Dependency and other issues to avoid the disaster of dimensionality

Pending Publication Date: 2020-04-10
华融融通(北京)科技有限公司
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Problems solved by technology

However, the disadvantage is that these public opinion information exists in the form of unstructured texts. When credit personnel dig useful information in it, the available technologies and tools are scarce, and they often ...

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  • Public opinion information extraction and knowledge base generation method based on natural language processing
  • Public opinion information extraction and knowledge base generation method based on natural language processing
  • Public opinion information extraction and knowledge base generation method based on natural language processing

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Embodiment Construction

[0032] The technical solutions of the present invention will be further described below in conjunction with specific embodiments.

[0033] A method for extracting public opinion information and generating a knowledge base based on natural language processing in the present invention, such as figure 1 shown, including the following steps:

[0034] Step 1. Text preprocessing

[0035] Text preprocessing is a basic and necessary step in unstructured data processing. It mainly reduces the negative impact of noisy data and improves the model by removing characters without entity semantics and filtering stop words after word segmentation. generalization ability. Therefore, the selected data preprocessing methods are mainly character cleaning, word segmentation and stop word removal.

[0036]Character cleaning. Characters such as commas, periods, and quotation marks in the text represent the pauses and connections of sentences, which have no practical meaning in semantic analysis ...

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Abstract

The invention discloses a public opinion information extraction and knowledge base generation method based on natural language processing. The public opinion information extraction and knowledge basegeneration method comprises the following steps of 1, text preprocessing; 2, named entity recognition: identifying company institution names and names, and finishing named entity recognition by adopting a neural network-based method; 3, relationship extraction: extracting six types of relationships in the financial field by adopting a feature layer + GRU + Attention; 4, entity linking; a Jaro winker distance method is adopted, and the distance between a link entity and a target entity is calculated to judge whether the link entity and the target entity are the same entity or not, so that entity disambiguation is achieved. According to the method, an end-to-end model and a feature extraction input class model are combined, a one-stop process from financial unstructured text to structured data storage is constructed, financial news context information is fully utilized, knowledge is extracted with fewer parameters and faster training prediction speed, and good performance is achieved inthe field of financial public opinion information.

Description

technical field [0001] The present invention is a public opinion information extraction and knowledge base generation method based on natural language processing, which involves entity recognition, relationship extraction, entity linking and other technologies in the field of financial information, and specifically relates to a method from information extraction to knowledge generation for corporate public opinion news A set of processes and methods. Background technique [0002] Due to the current diversification of investment entities and the development of enterprise management conglomerates, the relationship between enterprises is becoming more and more complex, and it is not limited to regions and industries, and is highly concealed. For financial institutions such as commercial banks, if enterprises deliberately conceal information when lending, it will be difficult for banks to grasp the real information, resulting in excessive credit extension, multi-credit extension...

Claims

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Application Information

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IPC IPC(8): G06F16/33G06F16/36
CPCG06F16/3335G06F16/367G06F16/374
Inventor 路世伦闫晨巍仵伟强周金黄钟丽莉万谊强
Owner 华融融通(北京)科技有限公司
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