Automatic enterprise data clustering method and system

Abstract

The invention relates to an automatic enterprise data clustering method and system. The automatic enterprise data clustering method comprises the steps that relevant data of enterprises is obtained; the relevant data of the enterprises is preprocessed and stored; text vectors are obtained from the processed relevant data of the enterprises; the text vectors are classified and clustered according to a K-Means algorithm. The accuracy and reliability of data sources are ensured by obtaining massive reliable relevant data of the enterprises, the enterprises are preprocessed by utilizing an unsupervised learning algorithm based machine learning technology, data storage is performed by utilizing HAFS, and automatic and reliability clustering is ensured. A natural language is adopted for data analysis, the text vectors and weights corresponding to the text vectors are obtained, the text vectors are automatically clustered from the massive data based on K value optimization and classificationmodels of specialists, it is ensured that the clustering supports the demand meeting actual applications, and automatic and available clustering is ensured.

Description

technical field [0001] The present invention relates to a method for processing enterprise data, more specifically to a method and system for automatic clustering of enterprise data. Background technique [0002] Enterprise data generally refers to all information and materials related to enterprise operations, including company profiles, product information, operating data, research results, etc., many of which involve commercial secrets. Generally speaking, enterprise data refers to enterprise data in a narrow sense, which generally only includes Company overview, including company business scope, contact information, enterprise size, etc., is usually public data. Enterprise data acquisition channels are divided into centralized and distributed. The centralized type is generally released by a unified government department, such as the data of the Bureau of Industry and Commerce and the Bureau of Statistics. It is authoritative and comprehensive, but the content of the dat...

AI Technical Summary

Problems solved by technology

[0003] At present, data and information are overflowing on the Internet, and enterprise data is even more disorganized. At this stage, the methods of processing these enterprise data are mostly in the manual stage, and the more advanced ones can only be semi-automatic. Classifying data still requires Manual assistance processing, in the face of massive enterprise data, the efficiency of classification is low, and the accuracy rate is also low

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