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

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...

AI Technical Summary

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 rely on manual browsing and query. The depth of investigation and query efficiency are limited, and it is difficult to satisfy The growing demand of financial institutions for the dynamic query of group customer related information

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