Company name matching method and device, computer equipment and storage medium

Abstract

The invention relates to a company name matching method and device, computer equipment and a storage medium. The company name matching method comprises the following steps: S1, receiving a company name submitted by a user; S2, performing word segmentation on the company name, and calculating the frequency and weight of words according to a word segmentation structure; S3, constructing a point-edgerelationship by taking the company name as a point and the same word as an edge; S4, for two company names with the same side relationship, calculating the Leivelstein distance similarity, and calculating the cosine distance similarity of the two company names according to the word weight; S5, filtering out edges lower than a threshold value, and quantifying the similarity of company names; S6, calculating a connected graph according to the filtered edge data, dividing the data, and finding out similar or same company names; according to the company name matching method and device, the computer equipment and the storage medium, pairwise calculation is avoided by constructing the edge relationship, so that the calculation amount is greatly reduced, and the calculation efficiency and the calculation accuracy are improved.

Description

technical field [0001] The invention relates to the technical field of software development, in particular to a company name matching method, device, computer equipment and storage medium. Background technique [0002] The fuzzy matching of company names in large-scale data sets is to find out the collection of expressions of the same company in different company names in a large amount of company name data. In the prior art, the public fuzzy matching of company names uses artificial or word-segmenting algorithms to standardize company names and perform pairwise comparisons, without optimizing the number of pairwise comparisons. [0003] At present, there are few fuzzy matching algorithms for company names for large-scale data sets. The main reason is that there are many algorithms for pairwise comparison of company names. Slow or impossible to calculate, the comparison algorithm is relatively simple, and it is easy to be affected by some factors, resulting in inaccurate fu...

AI Technical Summary

Problems solved by technology

In the existing technology, the algorithm used in the fuzzy matching of public company names is manual or word segmentation, standardizing company names, pairwise comparison, and no optimization for reducing the number of pairwise comparisons

[0003] At present, there are few fuzzy matching algorithms for company names for large-scale data sets. The main reason is that there are many algorithms for pairwise comparison of company names. Slow or impossible to calculate, the comparison algorithm is relatively simple, and it is easy to be affected by certain factors, resulting in inaccurate fuzzy matching results

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