摘要
数据挖掘可以从海量的数据信息中挖掘潜在的、有价值的数据知识,为人们提供决策辅助支撑,比如可以为大学生推荐合适的职位。本文在大学生就业推荐中引入先进的卷积神经网络,其作为一种先进的数据挖掘算法,可以利用多层次、深度学习模式,准确的提取大学生招聘岗位信息,匹配大学生的个人专业或能力,该算法具有参数少、层数多等特点,分类速度比较快,实时性非常强。实验结果表明,该算法推荐准确度达到了98%,在大学生就业推荐应用上具有较强的优势。
data mining can mine potential and valuable data knowledge from massive data information,providing decision support for people,such as recommending suitable positions for college students.Based on the university students'employment recommended the introduction of advanced convolution neural network,as a kind of advanced data mining algorithm,and can make use of multi-level and deep learning model,accurate extraction of college students'job information,match the college students'personal or professional ability,the algorithm has the characteristics of less parameters,layer number,classification speed is faster,real-time is very strong.The experimental results show that the recommendation accuracy of the algorithm reaches 98%,and it has a strong advantage in the application of college students'employment recommendation.
出处
《数码设计》
2019年第14期23-24,共2页
Peak Data Science
关键词
数据挖掘
大学生就业推荐
分类
卷积核尺度
data mining
College student employment recommendation
Classification
Convolution kernel scale
