Research on the Characteristics of Industrial Talent Demand Depending on Big Data Technology

Abstract

For a long time, there is a mismatch between supply and demand for industrial talents, and it is difficult to achieve a dynamic balance between talent supply and job demand. This paper aims to mine and analyze the characteristics of industrial talent demand through big data technology, so as to provide skills training reference for talent supply and provide talents with high matching degree for job demand. In this paper, TF-IDF is used as a feature selection method to extract highly representative feature words to help distinguish different talent information data to a greater extent. In addition, combined with the construction method of statistical analysis, quantitative indexing analysis of talent information data is carried out, which enhances the expansion of label system and makes talent portraits more precise and accurate. Through the experimental research, it is proved that the research system of industrial talent demand characteristics proposed in this paper can effectively analyze and match the characteristics of industrial talents. Therefore, in the social employment and higher education, we can combine the methods proposed in this paper to assist decision-making, and promote the dynamic balance between the demand and supply of industrial talents.