基于深度学习的电力企业智能招聘系统的设计与实现  

Design and implementation of power enterprise intelligent recruitment system based on deep learning

作　　者：张晶[1] 郑鹏 张春艳 刘俊宇 陈辉 Zhang Jing;Zheng Peng;Zhang Chunyan;Liu Junyu;Chen Hui(State Grid Fushun Power Supply Company,Fushun 113008,Liaoning,China)

机构地区：[1]国网抚顺供电公司,辽宁抚顺113008

出　　处：《现代科学仪器》2021年第2期28-31,共4页Modern Scientific Instruments

摘　　要：电力企业智能招聘系统对电力企业招贤纳才,提高电力企业市场竞争力具有至关重要的作用。本文将卷积神经网络作用于智能招聘系统原始图像,采用K均值聚类算法对图像进行识别,同时对招聘系统的用户管理模块、信息检索模块、求职管理模块以及安全验证模块进行了设计与实现。将深度学习的经典算法卷积神经网络应用于智能招聘系统中使得智能招聘系统的安全性、智能性得到了很大程度的提升,对智能招聘系统的设计具有一定的实用价值。The intelligent recruitment system plays an important role in recruiting talents and improving market competitiveness of power enterprises.In this paper,convolution neural network is applied to the original image of intelligent recruitment system,and K-means clustering algorithm is used to identify the image.Meanwhile,the user management module,information retrieval module,job search management module and security verification module of the recruitment system are designed and implemented.The application of convolution neural network,a classical algorithm of deep learning,in intelligent recruitment system makes the security and intelligence of intelligent recruitment system improved to a great extent,which has certain practical value for the design of intelligent recruitment system.

关 键 词：深度学习 智能招聘系统 卷积神经网络 K均值聚类算法 

分 类 号：D035.3[政治法律—政治学]