基于大数据的软件行业招聘市场需求预测

Demand Forecast of Recruitment Market in Software Industry Based on Big Data

为更好地解决招聘市场供需知识不对称问题,本文面向软件行业招聘领域,将多源跨平台的网络招聘信息进行自动采集与集成。首先,结合自然语言处理技术与招聘领域知识,对招聘信息中的企业、职位进行实体识别和关系抽取;其次,采用隐含狄利克雷分布(Latent Dirichlet Allocation,LDA)模型构建招聘需求和招聘主题之间的语义关系;最后,综合隐马尔科夫模型、深度学习方法对招聘市场需求进行预测,以期为招聘企业、求职者以及高校提供一定的参考作用。

In order to better resolve the problem of knowledge asymmetry between supply and demand in the recruitment market,this paper automatically collects and integrates multi-source and cross platform online recruitment information for the recruitment field of software industry.Firstly,combined with natural language processing technology and recruitment domain knowledge,entity recognition and relationship extraction are carried out for enterprises and positions in recruitment information;Secondly,LDA model is used to construct the semantic relationship between recruitment requirements and recruitment topics;Finally,the hidden Markov model and deep learning method are integrated to predict the demand of the recruitment market,in order to provide some reference for recruitment enterprises,job seekers and colleges and universities.