基于用户兴趣模型的大学生就业信息推荐方法
A Recommendation Method for College Student Employment Information Based on User Interest Model
南楠 1张玉香 1吴冉1
作者信息
- 1. 济宁职业技术学院,山东 济宁 272103
- 折叠
摘要
为提高推荐就业信息与大学生偏好就业信息的匹配程度,文章将个体就业需求作为前提条件,设计一种基于用户兴趣模型的大学生就业信息推荐方法.首先,利用兴趣模型中的关联规则,对高校提供的就业信息中兴趣特征点进行匹配;其次,在既定的分类规则下,根据就业文本信息的内容对其进行类别划分;最后,根据用户浏览高校就业信息、在就业招聘界面的停留时间等,针对大学生偏好进行计算.对比实验结果表明:本文中设计的推荐方法应用效果良好,按照规范使用该方法进行大学生就业信息推荐,能够增加推荐就业信息与大学生偏好就业信息的匹配程度,为大学生提供更加优质的就业服务,提高大学生就业质量.
Abstract
In order to improve the matching degree between recommended employment information and college student preference employment information,the article takes individual employment needs as a prerequisite and designs a college student employment information recommendation method based on user interest models.Firstly,using the association rules in the interest model,the interest feature points in the employment information provided by universities are matched;Secondly,under established classification rules,classify employment text information based on its content;Finally,based on the user's browsing of university employment information and the duration of stay in the employment recruitment interface,calculations are made based on the preferences of college students.The comparative experimental results show that the designed recommendation method has a good application effect.Using this method in accordance with regulations to recommend employment information for college students can increase the matching degree between recommended employment information and college students'preferred employment information,provide higher quality employment services for college students,and improve the quality of college students'employment.
关键词
用户兴趣模型/特征信息提取/就业文本信息/推荐方法/就业信息/大学生Key words
user interest model/feature information extraction/employment text information/recommended methods/employment information/university student引用本文复制引用
出版年
2024
NETL
NSTL
万方数据