Implementation of Recruitment Website Data Analysis System Based on Web Crawler

Yiyang Su, Xuanyu Hong, Shuxi Chen, Wei Song
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引用次数: 1

Abstract

With continuous development of science and technology, China is in the era of big data. In order to extract useful information from massive data, we must use data analysis system. The data analysis system greatly improves the use efficiency of data, and can get the hidden information in the data through the analysis of some complex data. This topic designs a recruitment website data analysis system based on web crawler, uses web crawler to collect the recruitment information in the recruitment website, analyzes the recruitment information, and finally displays the relevant information. The system uses the proceptron algorithm in deep learning to realize the salary prediction function for job seekers. In this system, the crawler function is written in Python language, and multi-threaded, anti-crawler and other technologies are used to crawl the data of the recruitment website. The application of this system can extract, store, analyze and display the complex and diverse recruitment information in the recruitment website, so that job seekers can more comprehensively understand the post information and find the most suitable job.
基于Web爬虫的招聘网站数据分析系统的实现
随着科技的不断发展,中国已经进入了大数据时代。为了从海量数据中提取有用的信息,必须使用数据分析系统。数据分析系统大大提高了数据的利用效率,通过对一些复杂数据的分析,可以得到数据中隐藏的信息。本课题设计了一个基于网络爬虫的招聘网站数据分析系统,利用网络爬虫对招聘网站中的招聘信息进行采集,对招聘信息进行分析,最后显示相关信息。系统采用深度学习中的感知器算法,实现求职者薪酬预测功能。本系统采用Python语言编写爬虫函数,并采用多线程、反爬虫等技术对招聘网站的数据进行抓取。本系统的应用可以对招聘网站中复杂多样的招聘信息进行提取、存储、分析和展示,使求职者能够更全面地了解岗位信息,找到最适合自己的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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