Enterprise industry classification method

Abstract

The invention discloses an enterprise industry classification method. According to the method, main business keywords of enterprises are effectively extracted by utilizing semi-supervised learning-based image split clustering algorithm, the extracted keywords are used as features on the basis of a gradient enhancement decision-making tree, and a training cascade classifier is used for classifyingthe enterprises according to industries, so that the problem that artificial classification is tedious is solved. The method specifically comprises the following steps of: 1) extracting main businesskeywords of enterprises by utilizing a word vector and a semi-supervised image split clustering algorithm, getting rid of junk words and constructing a keyword library; and 2) inputting the extractedkeywords which are taken as features into a training cascade classifier, the enterprises are classified by each level of classifier, and the unclassified enterprises are classified according to the next level of classifier. According to the method, keywords can be automatically constructed, updated and classified, the problem of classifying millions and millions of enterprise industries is solved,and the problem of artificial labelling is effectively solved.

Description

technical field [0001] The present invention relates to the research field of data classification methods, and more specifically, relates to the extraction of industry keywords. In the case that the business scope of the enterprise overlaps with multiple industry descriptions, the fusion of semi-supervised graph splitting and clustering and cascading gradient boosting decision trees The enterprise industry classification method. Background technique [0002] In the industry classification standard issued by the National Bureau of Statistics of the People's Republic of China in 2013, it is divided into 20 first-level industries and 96 second-level industries. The industry label of an enterprise is an important field, and there are tens of millions of enterprises across the country, and many enterprises are incubated every day. How to quickly classify enterprises by industry is an important issue. In the previous industry classification norms, the industry to which an enterpr...

AI Technical Summary

Problems solved by technology

In addition to this, a single classifier model relies too much on the coverage of sample descriptions, and is less accurate when classifying a new sample of a description that has never appeared before.

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