Optimisation of the training path of college students’ education management talents based on data mining algorithm

Abstract

Network information development speeds up digital and text mining and influences the optimization of university talent training. We analyze the basic process and main text mining algorithms in this paper and combine the bag-of-words model and TF-IDE to complete the vectorization of text information. The model for generating document topics, i.e. LDA topic model, is refined and analyzed in terms of sampling methods. Analyze the degree of influence of education management talent skill development on other professional skills using quantitative means. Analyzing the education management curriculum system and talent cultivation characteristics, the cultivation of college students’ education management talents involves several skills, including communication skills, organizational skills, teamwork, and the ability to control the overall situation. Problem-solving and learning abilities are given greater attention regarding professionalism, with 85.3% and 82.5%, respectively.

Keywords

• text mining
• information vectorization
• tf-idf
• talent development
• lda topic model
• 97q70