%0 Journal Article
%T 基于企业网络招聘的人才需求文本挖掘——以统计学为例<br>Talent Demand Text Mining Based on Enterprise Online Recruitment—Taking Statistics as an Example
%A 屈文鑫
%A 王锦权
%J Statistics and Applications
%P 954-964
%@ 2325-226X
%D 2024
%I Hans Publishing
%R 10.12677/sa.2024.133097
%X 大数据时代的到来，带来了数据形式和数据结构的革新，也给统计学以收集、整理和分析数据为基础的专业创造了有利的发展机会。但随着互联网技术的迅速发展，如人工智能、金融科技、大数据分析等新兴专业也不断涌现，这也给传统的统计学专业人才培养和市场需求造成一定的冲击。本文通过数据挖掘方法分析企业网络招聘文本，理清统计专业人才需求特征，从而为学生求职和高校教学提供依据。研究分为两个阶段：数据收集与预处理和深入挖掘招聘信息。结果显示，企业对应聘者的能力要求分为数据分析、协同沟通和生产管理三类；岗位类型分为业务类和技术类。<br />
The arrival of the big data era has brought about innovations in data forms and structures, and has also created favorable development opportunities for statistics professionals based on data collection, organization, and analysis. However, with the rapid development of Internet technology, emerging majors such as artificial intelligence, financial technology and big data analysis are also emerging, which also has a certain impact on the training of traditional statistics professionals and market demand. This article analyzes enterprise online recruitment texts through data mining methods, clarifies the characteristics of professional talent demand in statistics, and provides a basis for student job seeking and university teaching. The research is divided into two stages: Data collection and preprocessing, and in-depth exploration of recruitment information. The results show that the ability requirements of companies for job applicants can be divided into three categories: data analysis, collaborative communication, and production management; job types are divided into business and technical categories.
%K 网络招聘，统计学，人才需求，文本挖掘，LDA模型，文本聚类<br>Online Recruitment
%K Statistics
%K Talent Demand
%K Text Mining
%K LDA Model
%K Text Clustering
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=90795