Data Science Talents Mining from Online Recruitment Market in China Based on Data Mining Technique

Shiwei Yang, Ashardi Abas
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引用次数: 1

Abstract

As the country implements the big data strategy and accelerates the construction of a digital China, data science has entered a new and dynamic era, and the demand for data science talents in all walks of life is increasing. Many talent training departments have added undergraduates or degrees to data science talents, but it is still unclear whether they can meet social and economic development needs. This article aims to improve the quality and adaptability of data science talent training and conduct an in-depth analysis of the demand for data science talents. The technology used in this article is data mining technology. The data information of data science talents is crawled out of the demand information of data science talents on the recruitment website. The core content of network relationship visualization is proposed and analyzed through machine learning methods and text subject word extraction models. Achieve a comprehensive exploration of the demand for data science talents and provide a reference for talent training units to formulate data science talent training models.
基于数据挖掘技术的中国网络招聘市场数据科学人才挖掘
随着国家实施大数据战略,加快推进数字中国建设,数据科学进入了一个崭新的、充满活力的时代,各行各业对数据科学人才的需求日益增加。许多人才培养部门为数据科学人才增加了本科或学位,但他们是否能满足社会和经济发展的需求,目前还不清楚。本文旨在提高数据科学人才培养的质量和适应性,对数据科学人才的需求进行深入分析。本文使用的技术是数据挖掘技术。数据科学人才的数据信息是从招聘网站上的数据科学人才需求信息中抓取出来的。通过机器学习方法和文本主题词提取模型,提出并分析了网络关系可视化的核心内容。实现对数据科学人才需求的全面探索,为人才培养单位制定数据科学人才培养模式提供参考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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