基于BP神经网络的岗位信息匹配与数据挖掘技术研究与分析

F. Yuan
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引用次数: 0

摘要

随着互联网技术的不断发展,越来越多的公司开始使用招聘网站发布招聘信息,其中包含了大量的职位要求和求职者信息。如何从这些信息中高效地匹配合适的职位和求职者,已经成为企业和求职者面临的重要问题。本文将介绍一种基于BP神经网络的岗位信息匹配数据挖掘技术,通过分析岗位需求与应聘需求之间的直接关系,进行相应的匹配。同时,在匹配模型的算法研究中,通过对模型的训练,利用BP神经网络获得最优的层数和算法模型,从而保证匹配效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research and Analysis of Post Information Matching and Data Mining Technology Based on BP Neural Network
With the continuous development of Internet technology, more and more companies have begun to use recruitment websites to publish recruitment information, which contains a large number of job requirements and job seeker information. How to efficiently match suitable positions and job seekers from such information has become an important issue faced by enterprises and job seekers. This article will introduce a job information matching data mining technology based on BP neural network, and make corresponding matching by analyzing the direct relationship between job requirements and application requirements. At the same time, in the algorithm research of the matching model, the BP neural network is used to obtain the optimal number of layers and algorithm model through the training of the model, so as to ensure the matching effect.
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