Dynamic Optimization of Specialty Structure of Higher Education Based on Big Data Technology

Abstract

At present, big data technology with big data collection, big data analysis and mining, machine learning and other technologies as the core has been widely used in many fields. Through deep mining and analysis of massive data, big data technology can accurately predict and judge the supply and demand of disciplinary professionals, thus providing strong support for the dynamic optimization of the specialty structure of higher education. Through building life cycle management plan of specialty structure of universities and colleges, this article determines the source of big data acquisition, and by using Naive Bayes Classifier classifies and describes the talent status data of the industry, establishes the data model, and statistics the current distribution of professional and technical talents, and uses the time series prediction method to predict the future demand trend of all kinds of professional and technical personnel of enterprise, to provide strong support for specialty structure optimization, thereby to achieve higher education specialty structure dynamic optimization.