Artificial intelligence-based supply chain asset verification method, apparatus and device, and medium

Abstract

The invention relates to the field of artificial intelligence, and provides a supply chain asset verification method and device based on artificial intelligence, equipment and a medium, which can be used for performing word segmentation processing in combination with a word bank to establish a search keyword word bank and prepare for subsequent data processing, and establishing an abnormal feature word bank by utilizing preset features so as to improve the verification efficiency of supply chain assets. The to-be-checked data is input into the prediction model to assist in checking whether the supply chain assets have an abnormal risk, the abnormal feature word bank is used for checking the to-be-checked data to obtain a checking result, and when the checking result shows that the to-be-checked data does not pass the checking, the to-be-checked data is input into the prediction model, and output data of the prediction model is obtained to serve as a predicted risk level. According to the risk level and the verification result, the verification report is generated, and the automatic verification of the supply chain assets is realized in combination with a label and machine learning mode, so that manpower is effectively released, and the verification efficiency is improved. In addition, the invention also relates to a block chain technology, and each lexicon can be stored in a block chain node.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to a method, device, equipment and medium for verifying supply chain assets based on artificial intelligence. Background technique [0002] In many business scenarios involving the supply chain, business personnel usually need to read a large number of documents, including bills, documents, contracts, background information, etc., and manually review and evaluate assets based on the documents and accumulated transaction business data. [0003] The above processing methods mainly have the following problems: [0004] 1. Manual review is inefficient, time-consuming, and has a high error rate; [0005] 2. When looking for the required data from a large amount of data, it is necessary to read a lot of data, which is not only time-consuming and labor-intensive, but also has poor query results; [0006] 3. The effect of the verification mainly depends on the pers...

AI Technical Summary

Problems solved by technology

[0007] In view of the above, it is necessary to provide an artificial intelligence-based supply chain asset verification method, device, equipment and media, aiming at solving the problem of low efficiency and high error rate of supply chain asset verification

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