Improved high-frequency occupational skill life curve clustering method based on K-Means algorithm

Abstract

The invention discloses an improved high-frequency occupational skill life curve clustering method based on a K-Means algorithm, and the method is characterized by comprising the following steps: 1) crawling user information to form a user document library; 2) mining high-frequency occupational skills; 3) constructing a high-frequency professional skill life curve; 4) selecting K occupational skill life curve clustering centers by using a density peak algorithm; 5) clustering the occupational skill life curves by using a K-Means algorithm; 6) evaluating a clustering result by adopting a Thevenberg D index, if the evaluation is unqualified, increasing the number K of occupational skill life curve clustering centers, returning to the step 4, and entering the next step if the evaluation is qualified; 7) obtaining a final high-frequency occupational skill life curve clustering result. Through defining the high-frequency occupational skill life curve, the density peak algorithm is used forselecting the appropriate clustering center point, then the K-Means algorithm is used for clustering, and then occupational skills similar to the life curve are found out stably and effectively.

Description

technical field [0001] The invention relates to the field of data mining, in particular to an improved high-frequency vocational skill life curve clustering method based on the K-Means algorithm. Background technique [0002] The life curve of a professional skill is affected by many factors, such as the difficulty of mastering the professional skill, the social demand for the professional skill, the physical fitness requirements of the professional skill and the social recognition of the professional skill degree and other aspects of the impact. Therefore, it is very difficult to draw the life curve of professional skills. However, with the development of the Internet, social networking platforms have become an indispensable and important part of the development of the Internet. Professional social networking sites contain a large number of users' professional information. For example, the skills mastered by the user, the number of likes of the skill mastered by other use...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that it is difficult to describe the life curve of professional skills, and it is difficult to select the center point of the life curve clustering of professional skills, to provide a model for describing the life curve of high-frequency vocational skills and to provide efficient and stable clustering method

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