Natural language processing technology-based bad asset operation knowledge management method

Abstract

The invention discloses a natural language processing technology-based bad asset operation management method for an asset management company. The method comprises two parts including data importing inknowledge base construction and deep learning and PageRank-based keyword extraction. A new word model is discovered by utilizing a specific word bank and an HMM to perform word segmentation processing on bad asset operation knowledge, so that the text word segmentation accuracy is improved and a perfecter text word bank is established; word vectors are trained through a deep learning method, so that the phenomenon of "curse of dimensionality" represented with the word vectors can be avoided, information of vocabulary contexts can be fully mined, and relationships between words can be obtained; and based on an improved PageRank algorithm, a topology matrix of word connection is obtained according to a word sequence relationship in a specific contract, cosine values between the word vectorsserve as connection weights of the words, word vector information obtained by training the word bank is fully utilized, and a vocabulary relative position relationship in a text is mined, so that a powerful theoretical basis is provided.

Description

technical field [0001] The invention relates to a knowledge management method for non-performing assets management based on natural language processing technology, relates to natural language processing technology in the financial field, and specifically relates to a knowledge management method for asset management companies in the field of non-performing assets management. Background technique [0002] As an integral part of the domestic financial market, the non-performing asset management business plays an important role in maintaining the stability of the financial ecosystem and eliminating systemic risks. It is a stabilizer and fire extinguisher for the smooth operation of the domestic economy. The four major asset management companies (AMCs) initiated and established by the Ministry of Finance are the main body of non-performing asset management. Therefore, carrying out knowledge management of non-performing asset management knowledge in AMC companies will improve the l...

AI Technical Summary

Problems solved by technology

[0003] Due to the particularity of the industry, knowledge management in the field of non-performing asset management is also unique compared to knowledge management in traditional industries. Traditional knowledge management methods and systems cannot be well adapted to the non-performing asset management industry

It is mainly reflected in the following aspects: First, as the object of knowledge management, the knowledge structure of non-performing assets management is relatively complicated

Non-performing assets are usually packaged and sold by banks to asset management companies for disposal. As an asset management company whose main business is the disposal of non-performing assets, there are various ways to dispose of non-performing assets, such as restructuring, debt Therefore, the transaction structure of non-performing asset disposal is diversified, and the knowledge related to non-performing asset disposal covers a wide range and is complex; secondly, the data structure related to knowledge in the field of non-performing asset management is low

Due to the variety of disposal methods, and the customers are mainly medium and large enterprises, the number of customers is relatively small, and the scale of structured data such as transaction record data is small, while due diligence reports, overdue reports, management methods, meeting minutes, etc. , contracts, and comfort letters are all unstructured text data, and the scale is relatively large; third, the knowledge in the field of non-performing asset management is specific and industry-specific

Non-performing asset management business has high entry barriers and low degree of market participation. Therefore, the proportion of non-performing asset management knowledge in the financial field is relatively small, and it is not easy to obtain from the outside world. It relies more on the experience accumulated by the company's practitioners. Therefore, Common knowledge management tools in the financial field, such as industry semantic analysis solutions, industry knowledge organization and management solutions, are not fully applicable to asset management companies' knowledge management of non-performing assets

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