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引用本文:陈 亮.基于协同过滤算法的智能岗位分析系统的设计与实现[J].软件工程,2023,25(10):58-62.【点击复制】
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基于协同过滤算法的智能岗位分析系统的设计与实现
陈 亮
(大连东软信息学院, 辽宁 大连 116023)
摘 要: 针对现有招聘网站种类繁多和求职者无法快速根据自身特点找到适合岗位等问题,基于大数据技术和协同过滤算法,设计和实现了一个智能岗位分析系统。利用Python爬虫技术、虚拟化技术、Hadoop大数据平台及其生态组件进行数据处理,使用协同过滤算法进行智能分析,通过Axure RP和Sugar BI工具对结果数据进行可视化展示。经试用,系统能够很好地满足求职者的分析需求,提高了求职者精准查询招聘信息的效率。
关键词: 岗位分析;智能推荐;数据仓库;可视化
中图分类号: TP311    文献标识码: A
Design and Implementation of Intelligent Job Analysis System Based on Collaborative Filtering Algorithm
CHEN Liang
(Dalian Neusoft University of Information, Dalian 116023, China)
Abstract: This paper proposes to design and implement an intelligent job analysis system based on big data technology and collaborative filtering algorithm to address the issues of a wide variety of existing recruitment websites and the inability of job seekers to quickly find suitable positions based on their own characteristics. Python crawler technology, virtualization technology, Hadoop big data platform and its ecological components are used for data processing, collaborative filtering algorithm is used for intelligent analysis, and the resulting data is visualized through Axure RP and Sugar BI tools. After trial, the proposed system can well meet the analysis needs of job seekers and improve the efficiency of job seekers to accurately query recruitment information.
Keywords: job analysis; intelligent recommendation; data warehouse; visualization


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