摘要
为了帮助高等院校和大学生合理有效地利用网络上的就业信息资源,化解就业知识供需不对称问题,本文提出基于网络文本挖掘的"专业-岗位-知识点"的就业知识需求关系,并通过实验对其构建过程进行验证和分析。具体过程是通过对网络上与就业相关的文本进行挖掘,经过中文分词和语词标注,提取专业、岗位和知识点三者之间的关系,并形成"专业-岗位"、"岗位-知识点"的关系集合,最后以可视化的形式进行直观展现。本文通过实验证明"专业-岗位-知识点"的就业知识需求关系的构建具有较高的可行性,能在提高网络信息资源利用率的基础上,为高校和学生提供教学和学习参考,以应对市场的人才需求。
In order to help institutions of higher learning and college students make a reasonable and effective use of messy employment information resources on the network, and deal with the asymmetry of the supply-demand for employment knowledge, the paper puts forward a ＂professional-job-knowledge point＂ demand relationship of employment knowledge based on web text mining. Besides, the paper designs an experiment to verify and analyze the establishment process of the relationship. In detail, by mining the employment related text on the Internet, including Chinese word segmentation and words tagging, this paper extracts the relationships among professionals, jobs and knowledge points, forms the collections of ＂professional-job＂ and ＂job-knowledge point＂ relationships, and displays them on the form of visualization. The experiment shows that the establishment process of the relationship has high feasibility of technique, and it provides reference for schools and students to teach and learn on the basis of improving web resources utilization. Therefore, they can response to the talent demand of the market well.
出处
《图书情报知识》
CSSCI
北大核心
2016年第1期94-100,共7页
Documentation,Information & Knowledge
基金
国家社会科学基金重大项目"基于多维度聚合的网络资源知识发现研究"(13&ZD183)的成果之一
关键词
网络文本挖掘
就业知识
需求关系
关系提取
Web text mining；Employment knowledge；Demand relationship；Relationship extraction
