计算机科学
匹配(统计)
互联网
数据科学
探索者
模式(计算机接口)
数据挖掘
职位(财务)
决策树
万维网
人机交互
业务
统计
数学
法学
政治学
财务
出处
期刊:Journal of physics
[IOP Publishing]
日期:2021-11-01
卷期号:2066 (1): 012001-012001
被引量:3
标识
DOI:10.1088/1742-6596/2066/1/012001
摘要
Abstract With the rapid development of Internet technology and computer technology, network applications have been developed more and more, and have penetrated into all walks of life in society. The emergence of the networking of the talent market has made the scale of online recruitment increase, and the amount of data on the Internet has become larger and larger, and online recruitment has become the main channel for corporate recruitment. Therefore, how to use the massive online recruitment data to quickly and accurately find the corresponding information and explore the hidden knowledge mode is a very valuable research topic. Data mining (DM) is a technology for data analysis for large amounts of data. It can discover hidden, hidden, and potentially useful knowledge hidden in the data from the vague, noisy, and random mass data, and build relevant Model, realize prediction, etc. The characteristics of data mining technology (DMT) are very suitable for the analysis of online recruitment information, research on large amounts of information, and find out the knowledge in it for decision support. This article aims to study the accurate job matching system of the online recruitment platform based on DMT. Based on the analysis of the advantages of online recruitment, related DMT and the design principles of the online recruitment platform system, the data collected by Weka DM tools are analyzed. Analyzing and getting useful job positions is just to provide job seekers and corporate-related recruiters with useful job information. The experimental results show that the online recruitment platform system can complete the collection of online recruitment position information, and can realize the DM function, which has good practical application value.
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