Research on Optimization of Web Crawler Algorithm Based on Machine Learning
With the continuous development of the Internet,web crawlers are more and more widely used in the fields of information acquisition and data mining.At the same time,in Internet related applications,machine learning technology has become a very important means to achieve more efficient and accurate network crawling.However,existing web crawler algorithms still have many problems,such as low efficiency and easy to be banned.Therefore,this article analyzes and summarizes existing web crawler algorithms,identifies their problems and shortcomings,and proposes a machine learning based optimization method for web crawler algorithms to make them more intelligent and adaptive,in order to better meet the needs of practical applications.
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