Enterprise credit assessment method based on big data mining technology

Abstract

The invention relates to an enterprise credit assessment method based on the big data mining technology. The method includes the following steps that 1, credit information of an enterprise to be assessed is divided into five perspectives of basic assessment, human resources, products, after-sales services and outstanding payment, and multiple assessment keywords are set in each perspective; 2, all the assessment keywords of the enterprise to be assessed are acquired from multiple search engines through a crawler method, duplication eliminating is conducted through a fuzzy character string matching method, and the numbers of times that all the assessment keywords in all the perspectives appear are acquired; 3, each perspective is subjected to weighted grading according to the numbers of times that all the assessment keywords in all the perspectives appear, and normalization processing is conducted; 4, the grade obtained after the five perspectives of the enterprise to be assessed are normalized is displayed through a five-digit radar map. Compared with the prior art, the enterprise credit assessment method has the advantages that time is saved, data is comprehensive, consideration is comprehensive, and display is visual.

Description

technical field [0001] The invention relates to the field of enterprise credit evaluation, in particular to an enterprise credit evaluation method based on big data mining technology. Background technique [0002] The credit rating of an enterprise often has multiple factors such as word of mouth, product quality, personnel, and after-sales service. In previous technologies, how to evaluate the credit of an enterprise has not been clearly defined. If users want to know about the reputation of an enterprise, they need to actively search the Internet and find useful information from a large number of complicated web pages. However, searching for enterprise information on the Internet has the following defects. [0003] First, the enterprise content provided by a single search engine is not sufficient. When users search for information about a business, sometimes they can't even find anything relevant. Therefore, it is necessary to combine multi-search engines and multi-pla...

AI Technical Summary

Problems solved by technology

[0003] First, the enterprise content provided by a single search engine is not sufficient

When users search for information about a business, sometimes they can't even find anything relevant

Therefore, it is necessary to combine multi-search engines and multi-platform searches, which also increases the time consumed by users to understand corporate credit

[0004] Second, multiple search engines often include the same piece of information repeatedly, so there are often a lot of repetitions in the information obtained through network searches. Therefore, how to eliminate repeated information is a test of the user's endurance.

This is undoubtedly quite time consuming

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