基于大数据文本聚类关联的网络招聘信息挖掘

Online Recruitment Information Mining by Vast Amounts of Text Clustering and Associating

利用八爪鱼采集器自行爬取自2015年11月至2016年4月拉钩网近25万多条企业招聘信息,使用R语言编程,进行中文分词,设置频繁出现的领域干扰词,词频统计,文本向量化,再应用k-均值聚类及关联规则方法分析社会各行业对人才的能力及素质要求,直观化企业基本信息、职位类型、薪资水平、工作经验诸要求间的关联强度,为高校顺应社会对人才的需求、调整人才培养方案以及应届毕业生求职提出有益建议。

A large number of network recruitment information contains the knowledge of demand of employing units for employees, such as the requirement of talents＇ ability and quality, etc. Firstly, more than 25 thousands enterprises net recruitment information, from November 2015 to April 2016 in Lagou net is crawled out. Secondly, through setting frequent field disturbance terms, Chinese word segmentation, word frequency statistics, text vectorization, a k-means clustering using R language pro- gramming and Web diagram method are applied to excavate ability and quality requirements from so- cial various industries for talents, to describe the correlation strengths among enterprise basic informa- tion, the types of jobs, wages, job experience requirements for employees. Finally, some beneficial suggestions are put forward for colleges and universities to meet the social demand for talents and ad- just the talent training scheme, and some reference are provided for the fresh graduates to gain job in- formation.